<?xml version="1.0" encoding="UTF-8"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
  <url><loc>https://www.opentrain.ai/papers/the-geometry-of-dialogue-graphing-language-models-to-reveal-synergistic-teams-fo--arxiv-2510.26352/</loc><lastmod>2026-06-19T20:13:21.077Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/which-way-does-time-flow-a-psychophysics-grounded-evaluation-for-vision-language--arxiv-2510.26241/</loc><lastmod>2026-06-18T11:37:36.898Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/supervised-reinforcement-learning-from-expert-trajectories-to-step-wise-reasonin--arxiv-2510.25992/</loc><lastmod>2026-06-19T15:18:41.972Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/recap-reproducing-copyrighted-data-from-llms-training-with-an-agentic-pipeline--arxiv-2510.25941/</loc><lastmod>2026-06-19T03:15:39.192Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/through-the-judge-s-eyes-inferred-thinking-traces-improve-reliability-of-llm-rat--arxiv-2510.25860/</loc><lastmod>2026-06-19T12:44:39.991Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/theramind-a-strategic-and-adaptive-agent-for-longitudinal-psychological-counseli--arxiv-2510.25758/</loc><lastmod>2026-06-14T22:21:43.741Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/promediate-a-socio-cognitive-framework-for-evaluating-proactive-agents-in-multi--arxiv-2510.25224/</loc><lastmod>2026-06-19T07:56:38.935Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/activation-space-personality-steering-hybrid-layer-selection-for-stable-trait-co--arxiv-2511.03738/</loc><lastmod>2026-06-19T12:43:19.513Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/world-simulation-with-video-foundation-models-for-physical-ai--arxiv-2511.00062/</loc><lastmod>2026-06-19T15:27:01.705Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/do-large-language-models-grasp-the-grammar-evidence-from-grammar-book-guided-pro--arxiv-2510.24856/</loc><lastmod>2026-06-19T12:43:23.285Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agent-data-protocol-unifying-datasets-for-diverse-effective-fine-tuning-of-llm-a--arxiv-2510.24702/</loc><lastmod>2026-06-19T20:09:18.677Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ming-flash-omni-a-sparse-unified-architecture-for-multimodal-perception-and-gene--arxiv-2510.24821/</loc><lastmod>2026-06-18T11:12:39.775Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/lookahead-tree-based-rollouts-for-enhanced-trajectory-level-exploration-in-reinf--arxiv-2510.24302/</loc><lastmod>2026-06-19T15:24:41.124Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/musag-a-multimodal-german-sarcasm-dataset-with-full-modal-annotations--arxiv-2510.24178/</loc><lastmod>2026-06-19T13:20:43.925Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/gift-group-relative-implicit-fine-tuning-integrates-grpo-with-dpo-and-una--arxiv-2510.23868/</loc><lastmod>2026-06-19T12:42:58.211Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/your-llm-agents-are-temporally-blind-the-misalignment-between-tool-use-decisions--arxiv-2510.23853/</loc><lastmod>2026-06-19T15:17:54.809Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/beyond-understanding-evaluating-the-pragmatic-gap-in-llms-cultural-processing-of--arxiv-2510.23828/</loc><lastmod>2026-06-19T20:17:28.023Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/a-survey-of-data-agents-emerging-paradigm-or-overstated-hype--arxiv-2510.23587/</loc><lastmod>2026-06-19T20:05:44.410Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/robotarena-infty-scalable-robot-benchmarking-via-real-to-sim-translation--arxiv-2510.23571/</loc><lastmod>2026-06-19T05:53:31.032Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/echomind-an-interrelated-multi-level-benchmark-for-evaluating-empathetic-speech--arxiv-2510.22758/</loc><lastmod>2026-06-19T20:11:13.680Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/visjudge-bench-aesthetics-and-quality-assessment-of-visualizations--arxiv-2510.22373/</loc><lastmod>2026-06-18T11:11:04.064Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/viscoder2-building-multi-language-visualization-coding-agents--arxiv-2510.23642/</loc><lastmod>2026-06-19T15:19:59.893Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/parl-prompt-based-agents-for-reinforcement-learning--arxiv-2510.21306/</loc><lastmod>2026-06-19T15:21:51.088Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agentbound-securing-execution-boundaries-of-ai-agents--arxiv-2510.21236/</loc><lastmod>2026-06-19T15:29:28.193Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/estonian-native-large-language-model-benchmark--arxiv-2510.21193/</loc><lastmod>2026-06-19T06:09:14.905Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/support-contra-asymmetry-in-llm-explanations--arxiv-2510.21884/</loc><lastmod>2026-06-19T20:06:33.757Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/small-drafts-big-verdict-information-intensive-visual-reasoning-via-speculation--arxiv-2510.20812/</loc><lastmod>2026-06-19T20:17:22.129Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reloop-recursive-retrieval-with-multi-hop-reasoner-and-planners-for-heterogeneou--arxiv-2510.20505/</loc><lastmod>2026-06-19T20:10:48.148Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/robust-preference-alignment-via-directional-neighborhood-consensus--arxiv-2510.20498/</loc><lastmod>2026-06-19T20:21:20.284Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/creativityprism-a-holistic-evaluation-framework-for-large-language-model-creativ--arxiv-2510.20091/</loc><lastmod>2026-06-19T10:59:01.793Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/scaf-grpo-scaffolded-group-relative-policy-optimization-for-enhancing-llm-reason--arxiv-2510.19807/</loc><lastmod>2026-06-19T01:18:20.129Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/tooldreamer-instilling-llm-reasoning-into-tool-retrievers--arxiv-2510.19791/</loc><lastmod>2026-06-19T20:06:01.286Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/diffadapt-difficulty-adaptive-reasoning-for-token-efficient-llm-inference--arxiv-2510.19669/</loc><lastmod>2026-06-19T20:16:54.224Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/a-multi-faceted-analysis-of-cognitive-abilities-evaluating-prompt-methods-with-l--arxiv-2510.19139/</loc><lastmod>2026-06-19T20:04:28.675Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/grasp-any-region-towards-precise-contextual-pixel-understanding-for-multimodal-l--arxiv-2510.18876/</loc><lastmod>2026-06-19T20:20:41.465Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/a-model-can-help-itself-reward-free-self-training-for-llm-reasoning--arxiv-2510.18814/</loc><lastmod>2026-06-19T20:12:19.131Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/contrastive-decoding-mitigates-score-range-bias-in-llm-as-a-judge--arxiv-2510.18196/</loc><lastmod>2026-06-17T13:17:29.801Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/chain-of-thought-reasoning-improves-context-aware-translation-with-large-languag--arxiv-2510.18077/</loc><lastmod>2026-06-19T20:02:24.093Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/spacer-self-play-anchoring-with-centralized-reference-models--arxiv-2510.18060/</loc><lastmod>2026-06-19T20:03:36.327Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/annotation-efficient-universal-honesty-alignment--arxiv-2510.17509/</loc><lastmod>2026-06-19T20:21:24.553Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/streamingthinker-large-language-models-can-think-while-reading--arxiv-2510.17238/</loc><lastmod>2026-06-19T18:22:16.303Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/soft-masked-diffusion-language-models--arxiv-2510.17206/</loc><lastmod>2026-06-19T20:23:24.953Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/beacon-single-turn-diagnosis-and-mitigation-of-latent-sycophancy-in-large-langua--arxiv-2510.16727/</loc><lastmod>2026-06-19T15:21:46.936Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ma-sapo-multi-agent-reasoning-for-score-aware-prompt-optimization--arxiv-2510.16635/</loc><lastmod>2026-06-19T20:02:14.714Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/frugalprompt-reducing-contextual-overhead-in-large-language-models-via-token-att--arxiv-2510.16439/</loc><lastmod>2026-06-18T06:19:50.792Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/sentinelnet-safeguarding-multi-agent-collaboration-through-credit-based-dynamic--arxiv-2510.16219/</loc><lastmod>2026-06-19T20:22:24.197Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/polyskill-learning-generalizable-skills-through-polymorphic-abstraction--arxiv-2510.15863/</loc><lastmod>2026-06-19T20:04:15.143Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/hypospace-evaluating-llm-creativity-as-set-valued-hypothesis-generators-under-un--arxiv-2510.15614/</loc><lastmod>2026-06-19T07:24:56.339Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/sag-agent-enabling-long-horizon-reasoning-in-strategy-games-via-dynamic-knowledg--arxiv-2510.15259/</loc><lastmod>2026-06-19T20:22:21.934Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/guirilla-a-scalable-framework-for-automated-desktop-ui-exploration--arxiv-2510.16051/</loc><lastmod>2026-06-19T20:14:32.085Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/composition-grounded-data-synthesis-for-visual-reasoning--arxiv-2510.15040/</loc><lastmod>2026-06-19T20:19:05.230Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/information-gain-based-policy-optimization-a-simple-and-effective-approach-for-m--arxiv-2510.14967/</loc><lastmod>2026-06-19T20:03:12.858Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/beyond-multi-token-prediction-pretraining-llms-with-future-summaries--arxiv-2510.14751/</loc><lastmod>2026-06-19T20:04:40.516Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/e2edev-benchmarking-large-language-models-in-end-to-end-software-development-tas--arxiv-2510.14509/</loc><lastmod>2026-06-19T20:09:47.338Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/instructions-are-all-you-need-self-supervised-reinforcement-learning-for-instruc--arxiv-2510.14420/</loc><lastmod>2026-06-19T20:06:18.848Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/plurihoprag-exhaustive-recall-sensitive-qa-through-corpus-specific-document-stru--arxiv-2510.14377/</loc><lastmod>2026-06-19T20:08:14.253Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/codeevolve-an-open-source-evolutionary-coding-agent-for-algorithmic-discovery-an--arxiv-2510.14150/</loc><lastmod>2026-05-22T05:46:39.707Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mvcustom-multi-view-customized-diffusion-via-geometric-latent-rendering-and-comp--arxiv-2510.13702/</loc><lastmod>2026-06-19T20:06:54.515Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/closing-the-gap-between-text-and-speech-understanding-in-llms--arxiv-2510.13632/</loc><lastmod>2026-06-18T20:35:14.164Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/memotime-memory-augmented-temporal-knowledge-graph-enhanced-large-language-model--arxiv-2510.13614/</loc><lastmod>2026-06-19T09:29:25.331Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/assessing-llm-reasoning-through-implicit-causal-chain-discovery-in-climate-disco--arxiv-2510.13417/</loc><lastmod>2026-06-19T20:09:48.713Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mismatch-aware-guidance-for-robust-emotion-control-in-auto-regressive-tts-models--arxiv-2510.13293/</loc><lastmod>2026-06-19T11:48:18.274Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/putting-on-the-thinking-hats-a-survey-on-chain-of-thought-fine-tuning-from-the-p--arxiv-2510.13170/</loc><lastmod>2026-06-19T20:13:08.673Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/on-the-reasoning-abilities-of-masked-diffusion-language-models--arxiv-2510.13117/</loc><lastmod>2026-06-19T19:12:24.127Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/schema-for-in-context-learning--arxiv-2510.13905/</loc><lastmod>2026-06-19T07:47:39.830Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reveal-to-revise-explainable-bias-aware-generative-modeling-with-multimodal-atte--arxiv-2510.12957/</loc><lastmod>2026-06-19T20:01:44.063Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/narrow-finetuning-leaves-clearly-readable-traces-in-activation-differences--arxiv-2510.13900/</loc><lastmod>2026-06-19T20:02:56.420Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/toward-llm-supported-automated-assessment-of-critical-thinking-subskills--arxiv-2510.12915/</loc><lastmod>2026-06-19T20:05:39.546Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/beyond-black-box-interventions-latent-probing-for-faithful-retrieval-augmented-g--arxiv-2510.12460/</loc><lastmod>2026-06-19T20:07:14.057Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mcp-security-bench-msb-benchmarking-attacks-against-model-context-protocol-in-ll--arxiv-2510.15994/</loc><lastmod>2026-06-19T20:09:45.725Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/precise-attribute-intensity-control-in-large-language-models-via-targeted-repres--arxiv-2510.12121/</loc><lastmod>2026-06-19T20:01:39.460Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/too-open-for-opinion-embracing-open-endedness-in-large-language-models-for-socia--arxiv-2510.13884/</loc><lastmod>2026-06-19T20:01:44.249Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/r-wom-retrieval-augmented-world-model-for-computer-use-agents--arxiv-2510.11892/</loc><lastmod>2026-06-19T20:07:44.225Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/storybox-collaborative-multi-agent-simulation-for-hybrid-bottom-up-long-form-sto--arxiv-2510.11618/</loc><lastmod>2026-06-19T12:46:39.312Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/unlocking-the-potential-of-diffusion-language-models-through-template-infilling--arxiv-2510.13870/</loc><lastmod>2026-06-19T20:18:16.385Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/shishulm-achieving-optimal-and-efficient-parameterization-with-low-attention-tra--arxiv-2510.13860/</loc><lastmod>2026-06-07T07:19:39.707Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/dropvla-an-action-level-backdoor-attack-on-vision-language-action-models--arxiv-2510.10932/</loc><lastmod>2026-06-19T20:10:22.481Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/fml-bench-benchmarking-machine-learning-agents-for-scientific-research--arxiv-2510.10472/</loc><lastmod>2026-06-19T14:41:51.980Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/evoedit-evolving-null-space-alignment-for-robust-and-efficient-knowledge-editing--arxiv-2510.13851/</loc><lastmod>2026-06-19T20:15:38.428Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/language-steering-in-latent-space-to-mitigate-unintended-code-switching--arxiv-2510.13849/</loc><lastmod>2026-06-19T07:43:00.627Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/you-only-need-4-extra-tokens-synergistic-test-time-adaptation-for-llms--arxiv-2510.10223/</loc><lastmod>2026-06-19T20:01:29.772Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/diffusion-inspired-masked-fine-tuning-for-knowledge-injection-in-autoregressive--arxiv-2510.09885/</loc><lastmod>2026-06-19T20:03:16.462Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/graphmert-efficient-and-scalable-distillation-of-reliable-knowledge-graphs-from--arxiv-2510.09580/</loc><lastmod>2026-06-18T23:26:44.620Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/retraceqa-evaluating-reasoning-traces-of-small-language-models-in-commonsense-qu--arxiv-2510.09351/</loc><lastmod>2026-06-19T10:15:50.991Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/atlas-adaptive-trading-with-llm-agents-through-dynamic-prompt-optimization-and-m--arxiv-2510.15949/</loc><lastmod>2026-06-19T20:21:01.073Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/detecting-data-contamination-from-reinforcement-learning-post-training-for-large--arxiv-2510.09259/</loc><lastmod>2026-06-01T15:34:17.281Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/clear-roads-clear-vision-advancements-in-multi-weather-restoration-for-smart-tra--arxiv-2510.09228/</loc><lastmod>2026-06-19T20:15:46.645Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/multimodal-prompt-optimization-why-not-leverage-multiple-modalities-for-mllms--arxiv-2510.09201/</loc><lastmod>2026-06-19T20:04:44.612Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/finauditing-a-financial-taxonomy-structured-multi-document-benchmark-for-evaluat--arxiv-2510.08886/</loc><lastmod>2026-06-13T01:22:02.384Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mosaic-multi-agent-orchestration-for-task-intelligent-scientific-coding--arxiv-2510.08804/</loc><lastmod>2026-06-18T16:10:04.686Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/how-reliable-is-language-model-micro-benchmarking--arxiv-2510.08730/</loc><lastmod>2026-06-17T03:51:24.964Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/towards-unified-world-models-for-visual-navigation-via-memory-augmented-planning--arxiv-2510.08713/</loc><lastmod>2026-06-19T04:54:21.784Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/deepprune-parallel-scaling-without-inter-trace-redundancy--arxiv-2510.08483/</loc><lastmod>2026-06-15T09:40:25.516Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/if-probable-then-acceptable-understanding-conditional-acceptability-judgments-in--arxiv-2510.08388/</loc><lastmod>2026-06-19T20:03:56.460Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/lightreasoner-can-small-language-models-teach-large-language-models-reasoning--arxiv-2510.07962/</loc><lastmod>2026-06-19T07:24:58.718Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ace-attribution-controlled-knowledge-editing-for-multi-hop-factual-recall--arxiv-2510.07896/</loc><lastmod>2026-06-19T20:08:33.621Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mitigating-over-refusal-in-aligned-large-language-models-via-inference-time-acti--arxiv-2510.08646/</loc><lastmod>2026-06-19T14:00:18.595Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/curing-miracle-steps-in-llm-mathematical-reasoning-with-rubric-rewards--arxiv-2510.07774/</loc><lastmod>2026-06-19T20:18:44.125Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/econcausal-a-context-aware-causal-reasoning-benchmark-for-large-language-models--arxiv-2510.07231/</loc><lastmod>2026-06-19T20:08:40.584Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/search-r3-unifying-reasoning-and-embedding-in-large-language-models--arxiv-2510.07048/</loc><lastmod>2026-06-19T20:06:57.261Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/furina-a-fully-customizable-role-playing-benchmark-via-scalable-multi-agent-coll--arxiv-2510.06800/</loc><lastmod>2026-06-17T22:29:55.546Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/how-language-models-conflate-logical-validity-with-plausibility-a-representation--arxiv-2510.06700/</loc><lastmod>2026-06-18T15:06:53.692Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/pika-expert-level-synthetic-datasets-for-post-training-alignment-from-scratch--arxiv-2510.06670/</loc><lastmod>2026-06-17T12:07:31.014Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/peeking-inside-the-black-box-reinforcement-learning-for-explainable-and-accurate--arxiv-2510.06198/</loc><lastmod>2026-06-19T20:02:50.307Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/spectrum-tuning-post-training-for-distributional-coverage-and-in-context-steerab--arxiv-2510.06084/</loc><lastmod>2026-06-19T20:22:20.696Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/prompt-reinforcing-for-long-term-planning-of-large-language-models--arxiv-2510.05921/</loc><lastmod>2026-06-19T20:04:57.960Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/early-multimodal-prediction-of-cross-lingual-meme-virality-on-reddit-a-time-wind--arxiv-2510.05761/</loc><lastmod>2026-06-19T20:07:27.825Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/revisiting-self-play-preference-optimization-on-the-role-of-prompt-difficulty--arxiv-2510.05534/</loc><lastmod>2026-06-19T20:07:30.938Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/decoding-partial-differential-equations-cross-modal-adaptation-of-decoder-only-m--arxiv-2510.05278/</loc><lastmod>2026-06-19T20:03:45.723Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/slm-mux-orchestrating-small-language-models-for-reasoning--arxiv-2510.05077/</loc><lastmod>2026-06-19T20:12:28.579Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/titok-transfer-token-level-knowledge-via-contrastive-excess-to-transplant-lora--arxiv-2510.04682/</loc><lastmod>2026-06-19T20:12:21.486Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agentic-context-engineering-evolving-contexts-for-self-improving-language-models--arxiv-2510.04618/</loc><lastmod>2026-06-18T17:47:45.144Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ladir-latent-diffusion-enhances-llms-for-text-reasoning--arxiv-2510.04573/</loc><lastmod>2026-06-19T20:01:54.552Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/don-t-pass-k-a-bayesian-framework-for-large-language-model-evaluation--arxiv-2510.04265/</loc><lastmod>2026-06-19T20:10:13.607Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/alphaapollo-a-system-for-deep-agentic-reasoning--arxiv-2510.06261/</loc><lastmod>2026-06-19T10:10:22.726Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/turning-drift-into-constraint-robust-reasoning-alignment-in-non-stationary-envir--arxiv-2510.04142/</loc><lastmod>2026-06-19T20:10:57.988Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/poli-rl-a-point-to-list-reinforcement-learning-framework-for-conditional-semanti--arxiv-2510.04080/</loc><lastmod>2026-06-17T09:06:23.299Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/slow-fast-policy-optimization-reposition-before-update-for-llm-reasoning--arxiv-2510.04072/</loc><lastmod>2026-06-19T20:16:17.416Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/what-scales-in-cross-entropy-scaling-law--arxiv-2510.04067/</loc><lastmod>2026-06-19T20:07:17.644Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/person-centric-annotations-of-laion-400m-auditing-bias-and-its-transfer-to-model--arxiv-2510.03721/</loc><lastmod>2026-06-19T20:21:18.476Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/token-hidden-reward-steering-exploration-exploitation-in-group-relative-deep-rei--arxiv-2510.03669/</loc><lastmod>2026-06-19T20:17:25.862Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/monitorvlm-a-vision-language-framework-for-safety-violation-detection-in-mining--arxiv-2510.03666/</loc><lastmod>2026-06-19T20:16:16.492Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agenthub-a-registry-for-discoverable-verifiable-and-reproducible-ai-agents--arxiv-2510.03495/</loc><lastmod>2026-06-19T20:16:28.157Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/attention-aligned-reasoning-for-large-language-models--arxiv-2510.03223/</loc><lastmod>2026-06-19T20:24:25.368Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/unraveling-syntax-how-language-models-learn-context-free-grammars--arxiv-2510.02524/</loc><lastmod>2026-06-18T21:12:49.665Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/exgrpo-learning-to-reason-from-experience--arxiv-2510.02245/</loc><lastmod>2026-06-17T23:00:49.293Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/stockbench-can-llm-agents-trade-stocks-profitably-in-real-world-markets--arxiv-2510.02209/</loc><lastmod>2026-06-19T09:28:29.502Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/vl-kng-persistent-spatiotemporal-knowledge-graphs-from-egocentric-video-for-embo--arxiv-2510.01483/</loc><lastmod>2026-06-19T20:17:45.195Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/cures-from-gradient-analysis-to-efficient-curriculum-learning-for-reasoning-llms--arxiv-2510.01037/</loc><lastmod>2026-06-18T23:58:13.758Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/hypothesis-driven-feature-manifold-analysis-in-llms-via-supervised-multi-dimensi--arxiv-2510.01025/</loc><lastmod>2026-06-19T20:22:36.153Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/erase-to-improve-erasable-reinforcement-learning-for-search-augmented-llms--arxiv-2510.00861/</loc><lastmod>2026-06-19T20:22:47.854Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/managerbench-evaluating-the-safety-pragmatism-trade-off-in-autonomous-llms--arxiv-2510.00857/</loc><lastmod>2026-06-19T20:17:04.016Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/stochastic-self-organization-in-multi-agent-systems--arxiv-2510.00685/</loc><lastmod>2026-06-19T16:34:32.393Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reseek-a-self-correcting-framework-for-search-agents-with-instructive-rewards--arxiv-2510.00568/</loc><lastmod>2026-06-19T20:13:12.710Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/graph2eval-automatic-multimodal-task-generation-for-agents-via-knowledge-graphs--arxiv-2510.00507/</loc><lastmod>2026-06-19T20:07:42.670Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/training-large-language-models-to-reason-in-parallel-with-global-forking-tokens--arxiv-2510.05132/</loc><lastmod>2026-06-19T20:11:29.992Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/promptloop-plug-and-play-prompt-refinement-via-latent-feedback-for-diffusion-mod--arxiv-2510.00430/</loc><lastmod>2026-06-17T10:01:29.926Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/towards-self-evolving-benchmarks-synthesizing-agent-trajectories-via-test-time-e--arxiv-2510.00415/</loc><lastmod>2026-06-19T20:23:27.001Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/prefdisco-benchmarking-proactive-personalized-reasoning--arxiv-2510.00177/</loc><lastmod>2026-06-19T20:03:25.111Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/menlo-from-preferences-to-proficiency-evaluating-and-modeling-native-like-qualit--arxiv-2509.26601/</loc><lastmod>2026-06-18T16:00:25.661Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/offtopiceval-when-large-language-models-enter-the-wrong-chat-almost-always--arxiv-2509.26495/</loc><lastmod>2026-06-19T20:06:52.974Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/your-agent-may-misevolve-emergent-risks-in-self-evolving-llm-agents--arxiv-2509.26354/</loc><lastmod>2026-06-19T19:13:48.672Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/editreward-a-human-aligned-reward-model-for-instruction-guided-image-editing--arxiv-2509.26346/</loc><lastmod>2026-06-18T23:27:27.310Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/latent-thinking-optimization-your-latent-reasoning-language-model-secretly-encod--arxiv-2509.26314/</loc><lastmod>2026-06-19T20:02:46.362Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/semobridge-semantic-modality-bridge-for-efficient-few-shot-adaptation-of-clip--arxiv-2509.26036/</loc><lastmod>2026-06-19T20:05:36.644Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/asguard-activation-scaling-guard-to-mitigate-targeted-jailbreaking-attack--arxiv-2509.25843/</loc><lastmod>2026-06-19T20:17:29.693Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/overthinking-reduction-with-decoupled-rewards-and-curriculum-data-scheduling--arxiv-2509.25827/</loc><lastmod>2026-06-19T20:09:00.327Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/v-hub-a-benchmark-for-video-humor-understanding-from-vision-and-sound--arxiv-2509.25773/</loc><lastmod>2026-06-19T20:14:18.001Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ld-mole-learnable-dynamic-routing-for-mixture-of-lora-experts--arxiv-2509.25684/</loc><lastmod>2026-06-18T20:22:49.027Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/generative-value-conflicts-reveal-llm-priorities--arxiv-2509.25369/</loc><lastmod>2026-06-19T20:05:24.903Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/pretraining-with-hierarchical-memories-separating-long-tail-and-common-knowledge--arxiv-2510.02375/</loc><lastmod>2026-06-19T20:05:43.621Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/dive-into-the-agent-matrix-a-realistic-evaluation-of-self-replication-risk-in-ll--arxiv-2509.25302/</loc><lastmod>2026-06-16T01:36:09.404Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ultra-fast-language-generation-via-discrete-diffusion-divergence-instruct--arxiv-2509.25035/</loc><lastmod>2026-06-19T20:12:52.782Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agentic-exploration-of-physics-models--arxiv-2509.24978/</loc><lastmod>2026-06-19T20:04:16.324Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mobilellm-r1-exploring-the-limits-of-sub-billion-language-model-reasoners-with-o--arxiv-2509.24945/</loc><lastmod>2026-06-19T04:16:31.245Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/between-help-and-harm-an-evaluation-of-mental-health-crisis-handling-by-llms--arxiv-2509.24857/</loc><lastmod>2026-06-16T22:43:24.076Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/timeomni-1-incentivizing-complex-reasoning-with-time-series-in-large-language-mo--arxiv-2509.24803/</loc><lastmod>2026-06-19T13:35:58.648Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/inducing-dyslexia-in-vision-language-models--arxiv-2509.24597/</loc><lastmod>2026-06-19T20:12:53.688Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/diffuguard-how-intrinsic-safety-is-lost-and-found-in-diffusion-large-language-mo--arxiv-2509.24296/</loc><lastmod>2026-06-19T20:00:54.421Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/g-reasoner-foundation-models-for-unified-reasoning-over-graph-structured-knowled--arxiv-2509.24276/</loc><lastmod>2026-06-19T20:06:25.013Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/pragmatic-inference-for-moral-reasoning-acquisition-generalization-via-metapragm--arxiv-2509.24102/</loc><lastmod>2026-06-19T11:35:52.002Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/uncovering-grounding-ids-how-external-cues-shape-multimodal-binding--arxiv-2509.24072/</loc><lastmod>2026-06-16T14:42:16.980Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/spell-self-play-reinforcement-learning-for-evolving-long-context-language-models--arxiv-2509.23863/</loc><lastmod>2026-06-18T19:23:47.597Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/from-what-to-why-a-multi-agent-system-for-evidence-based-chemical-reaction-condi--arxiv-2509.23768/</loc><lastmod>2026-06-18T15:50:45.597Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/knowledge-level-consistency-reinforcement-learning-dual-fact-alignment-for-long--arxiv-2509.23765/</loc><lastmod>2026-06-19T16:44:38.307Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/safesearch-automated-red-teaming-of-llm-based-search-agents--arxiv-2509.23694/</loc><lastmod>2026-06-19T15:11:49.696Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/multi-modal-data-spectrum-multi-modal-datasets-are-multi-dimensional--arxiv-2509.23499/</loc><lastmod>2026-05-25T19:16:08.741Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mapping-overlaps-in-benchmarks-through-perplexity-in-the-wild--arxiv-2509.23488/</loc><lastmod>2026-06-17T07:20:11.400Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/your-models-have-thought-enough-training-large-reasoning-models-to-stop-overthin--arxiv-2509.23392/</loc><lastmod>2026-06-18T22:51:12.252Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/learning-to-reason-in-structured-in-context-environments-with-reinforcement-lear--arxiv-2509.23330/</loc><lastmod>2026-06-19T11:52:20.926Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/p-less-sampling-a-robust-hyperparameter-free-approach-for-llm-decoding--arxiv-2509.23234/</loc><lastmod>2026-06-19T11:51:33.061Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/autoep-llms-driven-automation-of-hyperparameter-evolution-for-metaheuristic-algo--arxiv-2509.23189/</loc><lastmod>2026-06-19T11:37:58.734Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/rhythm-reasoning-with-hierarchical-temporal-tokenization-for-human-mobility--arxiv-2509.23115/</loc><lastmod>2026-06-03T22:11:43.775Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/general-exploratory-bonus-for-optimistic-exploration-in-rlhf--arxiv-2510.03269/</loc><lastmod>2026-06-19T11:51:40.537Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/look-back-to-reason-forward-revisitable-memory-for-long-context-llm-agents--arxiv-2509.23040/</loc><lastmod>2026-05-22T07:35:57.305Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/soft-di-m-o-improving-one-step-discrete-image-generation-with-soft-embeddings--arxiv-2509.22925/</loc><lastmod>2026-06-19T11:53:38.554Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/heart-emotionally-driven-test-time-scaling-of-language-models--arxiv-2509.22876/</loc><lastmod>2026-06-19T11:35:33.417Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/critique-coder-enhancing-coder-models-by-critique-reinforcement-learning--arxiv-2509.22824/</loc><lastmod>2026-06-19T11:46:31.983Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/statex-enhancing-rnn-recall-via-post-training-state-expansion--arxiv-2509.22630/</loc><lastmod>2026-05-22T06:39:35.727Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/geosketch-a-neural-symbolic-approach-to-geometric-multimodal-reasoning-with-auxi--arxiv-2509.22460/</loc><lastmod>2026-06-19T04:15:32.758Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/featbench-towards-more-realistic-evaluation-of-feature-level-code-generation--arxiv-2509.22237/</loc><lastmod>2026-06-19T11:52:30.133Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/logipart-local-large-language-models-for-data-exploration-at-scale-with-logical--arxiv-2509.22211/</loc><lastmod>2026-06-19T21:52:12.560Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/bridging-draft-policy-misalignment-group-tree-optimization-for-speculative-decod--arxiv-2509.22134/</loc><lastmod>2026-06-19T11:52:46.280Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/scits-scientific-time-series-understanding-and-generation-with-llms--arxiv-2510.03255/</loc><lastmod>2026-06-16T14:51:00.552Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/march-evaluating-the-intersection-of-ambiguity-interpretation-and-multi-hop-infe--arxiv-2509.22750/</loc><lastmod>2026-06-16T23:58:12.488Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ergo-efficient-high-resolution-visual-understanding-for-vision-language-models--arxiv-2509.21991/</loc><lastmod>2026-05-22T07:24:21.295Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/multimodal-neural-operators-for-real-time-biomechanical-modelling-of-traumatic-b--arxiv-2510.03248/</loc><lastmod>2026-06-19T11:37:00.471Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/propersim-developing-proactive-and-personalized-ai-assistants-through-user-assis--arxiv-2509.21730/</loc><lastmod>2026-06-19T11:51:33.375Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reviewscore-misinformed-peer-review-detection-with-large-language-models--arxiv-2509.21679/</loc><lastmod>2026-06-19T11:42:06.589Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/tiny-but-mighty-a-software-hardware-co-design-approach-for-efficient-multimodal--arxiv-2510.05109/</loc><lastmod>2026-06-19T11:38:21.688Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/autoclimds-climate-data-science-agentic-ai-a-knowledge-graph-is-all-you-need--arxiv-2509.21553/</loc><lastmod>2026-06-17T07:18:34.278Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/updesh-synthesizing-grounded-instruction-tuning-data-for-13-indic-languages--arxiv-2509.21294/</loc><lastmod>2026-06-19T11:54:55.537Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/tree-search-for-llm-agent-reinforcement-learning--arxiv-2509.21240/</loc><lastmod>2026-06-19T13:56:36.647Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/sigma-semantically-informative-pre-training-for-skeleton-based-sign-language-und--arxiv-2509.21223/</loc><lastmod>2026-06-18T11:39:01.097Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/clause-agentic-neuro-symbolic-knowledge-graph-reasoning-via-dynamic-learnable-co--arxiv-2509.21035/</loc><lastmod>2026-06-18T06:47:36.412Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/predicting-llm-reasoning-performance-with-small-proxy-model--arxiv-2509.21013/</loc><lastmod>2026-06-19T11:38:44.986Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mars-toward-more-efficient-multi-agent-collaboration-for-llm-reasoning--arxiv-2509.20502/</loc><lastmod>2026-06-19T11:34:46.259Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/epidemiqs-prompt-to-paper-llm-agents-for-epidemic-modeling-and-analysis--arxiv-2510.00024/</loc><lastmod>2026-06-19T21:36:46.552Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/from-text-to-talk-audio-language-model-needs-non-autoregressive-joint-training--arxiv-2509.20072/</loc><lastmod>2026-06-19T11:37:25.881Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/slopal-a-60-million-word-slovak-parliamentary-corpus-with-aligned-speech-and-fin--arxiv-2509.19270/</loc><lastmod>2026-06-18T05:14:34.572Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/failure-makes-the-agent-stronger-enhancing-accuracy-through-structured-reflectio--arxiv-2509.18847/</loc><lastmod>2026-06-19T07:50:45.192Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/actions-speak-louder-than-prompts-a-large-scale-study-of-llms-for-graph-inferenc--arxiv-2509.18487/</loc><lastmod>2026-06-08T09:14:14.940Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/through-the-lens-of-human-human-collaboration-a-configurable-research-platform-f--arxiv-2509.18008/</loc><lastmod>2026-06-16T18:49:35.974Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/a-state-update-prompting-strategy-for-efficient-and-robust-multi-turn-dialogue--arxiv-2509.17766/</loc><lastmod>2026-06-19T11:46:31.450Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/better-late-than-never-meta-evaluation-of-latency-metrics-for-simultaneous-speec--arxiv-2509.17349/</loc><lastmod>2026-06-16T14:39:32.184Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/lifealign-lifelong-alignment-for-large-language-models-with-memory-augmented-foc--arxiv-2509.17183/</loc><lastmod>2026-06-19T11:48:39.797Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/airqa-a-comprehensive-qa-dataset-for-ai-research-with-instance-level-evaluation--arxiv-2509.16952/</loc><lastmod>2026-05-08T09:22:49.756Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/can-grpo-boost-complex-multimodal-table-understanding--arxiv-2509.16889/</loc><lastmod>2026-06-19T11:53:27.921Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/distribution-aligned-decoding-for-efficient-llm-task-adaptation--arxiv-2509.15888/</loc><lastmod>2026-06-19T13:36:26.132Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/beyond-words-enhancing-desire-emotion-and-sentiment-recognition-with-non-verbal--arxiv-2509.15540/</loc><lastmod>2026-06-19T11:44:54.650Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/atts-asynchronous-test-time-scaling-via-conformal-prediction--arxiv-2509.15148/</loc><lastmod>2026-06-19T11:34:30.584Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/georesponder-towards-building-geospatial-llms-for-time-critical-disaster-respons--arxiv-2509.19354/</loc><lastmod>2026-06-19T11:33:57.590Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reasoning-efficiently-through-adaptive-chain-of-thought-compression-a-self-optim--arxiv-2509.14093/</loc><lastmod>2026-06-19T11:47:42.008Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/see-think-act-teaching-multimodal-agents-to-effectively-interact-with-gui-by-ide--arxiv-2509.13615/</loc><lastmod>2026-06-19T11:52:12.599Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/resum-unlocking-long-horizon-search-intelligence-via-context-summarization--arxiv-2509.13313/</loc><lastmod>2026-06-18T21:06:30.844Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/from-next-token-prediction-to-strips-world-models--arxiv-2509.13389/</loc><lastmod>2026-06-19T18:44:43.849Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/learning-to-optimize-multi-objective-alignment-through-dynamic-reward-weighting--arxiv-2509.11452/</loc><lastmod>2026-06-19T11:42:17.967Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/no-answer-needed-predicting-llm-answer-accuracy-from-question-only-linear-probes--arxiv-2509.10625/</loc><lastmod>2026-06-19T11:46:15.393Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/the-illusion-of-diminishing-returns-measuring-long-horizon-execution-in-llms--arxiv-2509.09677/</loc><lastmod>2026-06-19T11:38:22.773Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/evolution-and-compression-in-llms-on-the-emergence-of-human-aligned-categorizati--arxiv-2509.08093/</loc><lastmod>2026-06-19T11:34:59.503Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/new-insights-into-optimal-alignment-of-acoustic-and-linguistic-representations-f--arxiv-2509.05609/</loc><lastmod>2026-06-19T11:38:53.265Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/post-training-large-language-models-for-diverse-high-quality-responses--arxiv-2509.04784/</loc><lastmod>2026-06-18T14:19:04.873Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/self-adaptive-dataset-construction-for-real-world-multimodal-safety-scenarios--arxiv-2509.04403/</loc><lastmod>2026-06-17T22:36:14.046Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mitigating-multimodal-hallucinations-via-gradient-based-self-reflection--arxiv-2509.03113/</loc><lastmod>2026-06-19T00:40:33.724Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/implicit-actor-critic-coupling-via-a-supervised-learning-framework-for-rlvr--arxiv-2509.02522/</loc><lastmod>2026-06-19T11:49:55.898Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/error-notebook-guided-training-free-part-retrieval-in-3d-cad-assemblies-via-visi--arxiv-2509.01350/</loc><lastmod>2026-06-18T04:44:41.647Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/tempcore-are-video-qa-benchmarks-temporally-grounded-a-frame-selection-sensitivi--arxiv-2509.01167/</loc><lastmod>2026-06-19T11:37:38.607Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/when-thinking-backfires-mechanistic-insights-into-reasoning-induced-misalignment--arxiv-2509.00544/</loc><lastmod>2026-06-19T11:53:23.451Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/on-the-theoretical-limitations-of-embedding-based-retrieval--arxiv-2508.21038/</loc><lastmod>2026-06-18T11:19:12.789Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/eo-1-an-open-unified-embodied-foundation-model-for-general-robot-control--arxiv-2508.21112/</loc><lastmod>2026-06-19T11:53:56.743Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/npg-muse-scaling-long-chain-of-thought-reasoning-with-np-hard-graph-problems--arxiv-2508.20373/</loc><lastmod>2026-06-19T21:04:15.962Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agentcoma-a-compositional-benchmark-mixing-commonsense-and-mathematical-reasonin--arxiv-2508.19988/</loc><lastmod>2026-06-17T03:02:26.705Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/diffusion-language-models-know-the-answer-before-decoding--arxiv-2508.19982/</loc><lastmod>2026-06-19T11:46:47.068Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/latextrans-structured-latex-translation-with-multi-agent-coordination--arxiv-2508.18791/</loc><lastmod>2026-06-18T19:38:25.878Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/vistawise-building-cost-effective-agent-with-cross-modal-knowledge-graph-for-min--arxiv-2508.18722/</loc><lastmod>2026-06-19T11:52:38.634Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/latent-self-consistency-for-reliable-majority-set-selection-in-short-and-long-an--arxiv-2508.18395/</loc><lastmod>2026-06-19T11:36:30.020Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/how-quantization-shapes-bias-in-large-language-models--arxiv-2508.18088/</loc><lastmod>2026-06-18T23:18:50.620Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ambisql-interactive-ambiguity-detection-and-resolution-for-text-to-sql--arxiv-2508.15276/</loc><lastmod>2026-06-19T06:23:55.124Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/quantization-meets-dllms-a-systematic-study-of-post-training-quantization-for-di--arxiv-2508.14896/</loc><lastmod>2026-06-19T11:39:38.962Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/chunks-as-arms-multi-armed-bandit-guided-sampling-for-long-context-llm-preferenc--arxiv-2508.13993/</loc><lastmod>2026-06-18T07:17:52.581Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/the-collaboration-paradox-why-generative-ai-requires-both-strategic-intelligence--arxiv-2508.13942/</loc><lastmod>2026-06-19T11:33:22.835Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/depth-breadth-synergy-in-rlvr-unlocking-llm-reasoning-gains-with-adaptive-explor--arxiv-2508.13755/</loc><lastmod>2026-06-17T06:18:31.233Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/breaking-the-sft-plateau-multimodal-structured-reinforcement-learning-for-chart--arxiv-2508.13587/</loc><lastmod>2026-06-19T11:46:54.068Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/taser-table-agents-for-schema-guided-extraction-and-recommendation--arxiv-2508.13404/</loc><lastmod>2026-06-18T20:26:01.037Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/taosr1-the-thinking-model-for-e-commerce-relevance-search--arxiv-2508.12365/</loc><lastmod>2026-06-19T11:42:27.720Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/core-measuring-multi-agent-llm-interaction-quality-under-game-theoretic-pressure--arxiv-2508.11915/</loc><lastmod>2026-06-19T17:12:20.838Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/safesieve-from-heuristics-to-experience-in-progressive-pruning-for-llm-based-mul--arxiv-2508.11733/</loc><lastmod>2026-06-19T11:36:53.047Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/craft-gui-curriculum-reinforced-agent-for-gui-tasks--arxiv-2508.11360/</loc><lastmod>2026-06-19T11:49:46.048Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agentic-design-review-system--arxiv-2508.10745/</loc><lastmod>2026-06-19T11:46:16.816Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/genom-ontology-matching-with-description-generation-and-large-language-model--arxiv-2508.10703/</loc><lastmod>2026-06-19T11:48:47.645Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/for-value-efficient-forward-only-data-valuation-for-finetuning-llms-and-vlms--arxiv-2508.10180/</loc><lastmod>2026-04-28T08:20:43.299Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/from-context-to-intent-reasoning-guided-function-level-code-completion--arxiv-2508.09537/</loc><lastmod>2026-06-19T11:30:43.178Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/peer-unified-process-outcome-reinforcement-learning-for-structured-empathetic-re--arxiv-2508.09521/</loc><lastmod>2026-06-19T11:46:27.954Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/iag-input-aware-backdoor-attack-on-vlm-based-visual-grounding--arxiv-2508.09456/</loc><lastmod>2026-06-19T18:58:23.209Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/segdac-visual-generalization-in-reinforcement-learning-via-dynamic-object-tokens--arxiv-2508.09325/</loc><lastmod>2026-05-25T22:21:02.258Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/feedback-driven-tool-use-improvements-in-large-language-models-via-automated-bui--arxiv-2508.08791/</loc><lastmod>2026-06-18T18:43:16.353Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/diver-a-multi-stage-approach-for-reasoning-intensive-information-retrieval--arxiv-2508.07995/</loc><lastmod>2026-06-19T09:12:31.196Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/1-2-3-check-enhancing-contextual-privacy-in-llm-via-multi-agent-reasoning--arxiv-2508.07667/</loc><lastmod>2026-06-19T11:39:27.115Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/klear-reasoner-advancing-reasoning-capability-via-gradient-preserving-clipping-p--arxiv-2508.07629/</loc><lastmod>2026-05-30T23:09:03.582Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/sevade-self-evolving-multi-agent-analysis-with-decoupled-evaluation-for-hallucin--arxiv-2508.06803/</loc><lastmod>2026-06-18T21:28:31.427Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/memp-exploring-agent-procedural-memory--arxiv-2508.06433/</loc><lastmod>2026-06-19T18:06:33.828Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ur-2-unify-rag-and-reasoning-through-reinforcement-learning--arxiv-2508.06165/</loc><lastmod>2026-06-18T22:14:57.260Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/evolvr-self-evolving-pairwise-reasoning-for-story-evaluation-to-enhance-generati--arxiv-2508.06046/</loc><lastmod>2026-06-19T11:31:33.751Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/groundact-can-llm-agents-ground-actions-in-environmental-states--arxiv-2508.05614/</loc><lastmod>2026-06-18T07:22:01.541Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mathsmith-towards-extremely-hard-mathematical-reasoning-by-forging-synthetic-pro--arxiv-2508.05592/</loc><lastmod>2026-06-19T11:46:37.686Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/not-all-errors-are-created-equal-ascot-addresses-late-stage-fragility-in-efficie--arxiv-2508.05282/</loc><lastmod>2026-06-19T11:36:18.499Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/tura-tool-augmented-unified-retrieval-agent-for-ai-search--arxiv-2508.04604/</loc><lastmod>2026-06-19T11:38:58.297Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/share-your-attention-transformer-weight-sharing-via-matrix-based-dictionary-lear--arxiv-2508.04581/</loc><lastmod>2026-06-19T11:52:33.987Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reasoningguard-safeguarding-large-reasoning-models-with-inference-time-safety-ah--arxiv-2508.04204/</loc><lastmod>2026-06-19T11:38:00.813Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/coact-1-computer-using-multi-agent-system-with-coding-actions--arxiv-2508.03923/</loc><lastmod>2026-06-19T10:36:26.901Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/molreasoner-toward-effective-and-interpretable-reasoning-for-molecular-llms--arxiv-2508.02066/</loc><lastmod>2026-06-19T11:46:20.626Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/a-theory-of-adaptive-scaffolding-for-llm-based-pedagogical-agents--arxiv-2508.01503/</loc><lastmod>2026-06-19T11:54:05.260Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/towards-efficient-medical-reasoning-with-minimal-fine-tuning-data--arxiv-2508.01450/</loc><lastmod>2026-06-19T11:37:00.813Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/cognitive-kernel-pro-a-framework-for-deep-research-agents-and-agent-foundation-m--arxiv-2508.00414/</loc><lastmod>2026-06-18T11:19:20.735Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/rl-plus-countering-capability-boundary-collapse-of-llms-in-reinforcement-learnin--arxiv-2508.00222/</loc><lastmod>2026-06-18T15:08:32.737Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/ui-agile-advancing-gui-agents-with-effective-reinforcement-learning-and-precise--arxiv-2507.22025/</loc><lastmod>2026-06-19T11:37:43.305Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/soft-head-selection-for-injecting-icl-derived-task-embeddings--arxiv-2507.20906/</loc><lastmod>2026-04-14T10:58:25.504Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mmgraphrag-bridging-vision-and-language-with-interpretable-multimodal-knowledge--arxiv-2507.20804/</loc><lastmod>2026-06-19T11:33:56.698Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/rod-tal-a-benchmark-for-answering-questions-in-romanian-driving-license-exams--arxiv-2507.19666/</loc><lastmod>2026-06-19T11:44:43.500Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/shop-r1-rewarding-llms-to-simulate-human-behavior-in-online-shopping-via-reinfor--arxiv-2507.17842/</loc><lastmod>2026-06-19T11:44:59.640Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/cascade-llm-powered-javascript-deobfuscator-at-google--arxiv-2507.17691/</loc><lastmod>2026-06-19T11:52:57.501Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/simlens-for-early-exit-in-large-language-models-eliciting-accurate-latent-predic--arxiv-2507.17618/</loc><lastmod>2026-06-18T12:03:29.698Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/triple-x-a-llm-based-multilingual-speech-recognition-system-for-the-interspeech2--arxiv-2507.17288/</loc><lastmod>2026-06-19T11:35:51.522Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/decoding-translation-related-functional-sequences-in-5-utrs-using-interpretable--arxiv-2507.16801/</loc><lastmod>2026-06-17T17:37:38.591Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/spirollm-finetuning-pretrained-llms-to-understand-spirogram-time-series-with-cli--arxiv-2507.16145/</loc><lastmod>2026-06-19T11:52:34.940Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/look-before-you-fuse-2d-guided-cross-modal-alignment-for-robust-3d-detection--arxiv-2507.16861/</loc><lastmod>2026-06-18T13:18:14.817Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/learning-to-extract-rational-evidence-via-reinforcement-learning-for-retrieval-a--arxiv-2507.15586/</loc><lastmod>2026-06-19T11:34:51.891Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/questa-expanding-reasoning-capacity-in-llms-via-question-augmentation--arxiv-2507.13266/</loc><lastmod>2026-06-19T11:41:39.193Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/let-s-think-in-two-steps-mitigating-agreement-bias-in-mllms-with-self-grounded-v--arxiv-2507.11662/</loc><lastmod>2026-06-18T14:29:55.997Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/openxrd-a-comprehensive-benchmark-framework-for-llm-mllm-xrd-question-answering--arxiv-2507.09155/</loc><lastmod>2026-06-19T06:13:37.921Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/toolregistry-a-protocol-agnostic-tool-management-library-for-function-calling-ll--arxiv-2507.10593/</loc><lastmod>2026-06-18T16:06:44.528Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/knowledge-fusion-via-bidirectional-information-aggregation--arxiv-2507.08704/</loc><lastmod>2026-06-19T11:48:20.824Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/frugalrag-less-is-more-in-rl-finetuning-for-multi-hop-question-answering--arxiv-2507.07634/</loc><lastmod>2026-06-19T11:42:31.717Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/spatialviz-bench-a-cognitively-grounded-benchmark-for-diagnosing-spatial-visuali--arxiv-2507.07610/</loc><lastmod>2026-06-18T21:21:48.354Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reward-models-can-improve-themselves-reward-guided-adversarial-failure-mode-disc--arxiv-2507.06419/</loc><lastmod>2026-06-19T01:06:42.241Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/optimus-a-robust-defense-framework-for-mitigating-toxicity-while-fine-tuning-con--arxiv-2507.05660/</loc><lastmod>2026-06-17T22:39:12.021Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/the-generalization-ridge-information-flow-in-natural-language-generation--arxiv-2507.05387/</loc><lastmod>2026-06-19T11:39:39.887Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agentic-vehicles-for-human-centered-mobility--arxiv-2507.04996/</loc><lastmod>2026-06-19T11:41:28.834Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/gdgb-a-benchmark-for-generative-dynamic-text-attributed-graph-learning--arxiv-2507.03267/</loc><lastmod>2026-06-19T11:38:41.200Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/intrinsic-fingerprint-of-llms-continue-training-is-not-all-you-need-to-steal-a-m--arxiv-2507.03014/</loc><lastmod>2026-06-18T15:10:57.640Z</lastmod></url>
</urlset>