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  <url><loc>https://www.opentrain.ai/papers/combinatorial-synthesis-scaling-code-rlvr-via-atomic-decomposition-and-recombina--arxiv-2605.31058/</loc><lastmod>2026-06-19T21:39:35.882Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/from-prompt-injection-to-persistent-control-defending-agentic-harness-against-tr--arxiv-2605.31042/</loc><lastmod>2026-06-19T21:40:16.469Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/towards-streaming-synchronized-spatial-audio-generation-via-autoregressive-diffu--arxiv-2605.30940/</loc><lastmod>2026-06-19T11:52:32.609Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mineexplorer-evaluating-open-world-exploration-of-mllm-agents-in-minecraft--arxiv-2605.30931/</loc><lastmod>2026-06-19T11:53:43.690Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/the-flip-side-of-rlhf-on-policy-feedback-for-reward-model-self-supervised-improv--arxiv-2605.30888/</loc><lastmod>2026-06-19T08:11:51.950Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/dmoe-dllms-with-learnable-block-experts--arxiv-2605.30876/</loc><lastmod>2026-06-19T09:49:42.911Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/distilling-llm-feedback-for-lean-theorem-proving--arxiv-2605.30861/</loc><lastmod>2026-06-19T21:39:50.059Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/hide-and-seek-in-trajectories-discovering-failure-signals-for-vla-runtime-monito--arxiv-2605.30834/</loc><lastmod>2026-06-19T11:52:34.702Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/function2scene-3d-indoor-scene-layout-from-functional-specifications--arxiv-2605.30819/</loc><lastmod>2026-06-19T21:39:30.538Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/mechvqa-benchmarking-and-enhancing-multimodal-llms-on-comprehensive-mechanical-d--arxiv-2605.30794/</loc><lastmod>2026-06-18T23:36:57.046Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/skill-is-not-one-size-fits-all-model-aware-skill-alignment-for-llm-agents--arxiv-2605.30723/</loc><lastmod>2026-06-19T21:39:23.364Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/a-multi-ai-agent-framework-enabling-end-to-end-finite-element-analysis-for-solid--arxiv-2606.00138/</loc><lastmod>2026-06-19T21:54:28.592Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/harness-updating-is-not-harness-benefit-disentangling-evolution-capabilities-in--arxiv-2605.30621/</loc><lastmod>2026-06-19T21:46:30.118Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/prior-availability-in-industrial-visual-sim-to-real-a-review-of-cad-guided-and-c--arxiv-2605.30581/</loc><lastmod>2026-06-19T21:16:55.384Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/memory-bound-but-not-bandwidth-limited-the-physical-ai-inference-gap-in-batch-1--arxiv-2605.30571/</loc><lastmod>2026-06-19T21:03:23.019Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/tiny-but-trusted-efficient-vision-language-reasoning-for-time-series-anomaly-det--arxiv-2605.30344/</loc><lastmod>2026-06-19T11:51:39.032Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/schgen-pcb-schematic-generation-with-semantic-grounded-code-representations--arxiv-2605.30345/</loc><lastmod>2026-06-19T04:38:43.617Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/unlocking-the-working-memory-of-large-language-models-for-latent-reasoning--arxiv-2605.30343/</loc><lastmod>2026-06-19T11:52:37.670Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/soundnessbench-can-your-ai-scientist-really-tell-good-research-ideas-from-bad-on--arxiv-2605.30329/</loc><lastmod>2026-06-19T21:15:17.917Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/reasoning-with-sampling-cutting-at-decision-points--arxiv-2605.30327/</loc><lastmod>2026-06-19T21:18:47.744Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/exploring-autonomous-agentic-data-engineering-for-model-specialization--arxiv-2605.30407/</loc><lastmod>2026-06-18T22:27:49.793Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/medcase-structured-a-text-to-fhir-dataset-for-benchmarking-diagnostic-reasoning--arxiv-2605.30295/</loc><lastmod>2026-06-19T21:01:46.362Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/qwen-vla-unifying-vision-language-action-modeling-across-tasks-environments-and--arxiv-2605.30280/</loc><lastmod>2026-06-19T21:20:28.481Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/loong-a-human-like-long-document-translation-agent-with-observe-and-act-adaptive--arxiv-2605.30274/</loc><lastmod>2026-06-19T21:17:21.604Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/llumi-improving-llm-writing-assistance-for-mental-health-support-with-online-com--arxiv-2605.30273/</loc><lastmod>2026-06-19T15:27:02.071Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/phygenhoi-physically-aware-4d-generation-of-dynamic-human-object-interactions--arxiv-2605.30268/</loc><lastmod>2026-06-19T11:13:44.974Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/minwm-a-full-stack-open-source-framework-for-real-time-interactive-video-world-m--arxiv-2605.30263/</loc><lastmod>2026-06-19T14:42:24.740Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/how-lora-remembers-a-parametric-memory-law-for-llm-finetuning--arxiv-2605.30260/</loc><lastmod>2026-06-19T01:26:35.731Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/stable-layers-fine-tuning-image-layer-decomposition-models-with-vlm-scored-reinf--arxiv-2605.30257/</loc><lastmod>2026-06-19T11:53:37.106Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/same-evidence-different-answers-canonical-context-on-policy-distillation-for-mul--arxiv-2605.30251/</loc><lastmod>2026-06-19T06:31:50.589Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/knowing-what-to-solve-before-how-preplan-empowered-llm-mathematical-reasoning--arxiv-2605.30245/</loc><lastmod>2026-06-19T01:26:26.925Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/do-language-models-track-entities-across-state-changes--arxiv-2605.30233/</loc><lastmod>2026-06-19T11:18:23.760Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/how-s-it-going-reinforcement-learning-in-language-models-recruits-a-functional-w--arxiv-2605.30232/</loc><lastmod>2026-06-19T21:17:20.277Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/beyond-3d-vqas-injecting-3d-spatial-priors-into-vision-language-models-for-enhan--arxiv-2605.30231/</loc><lastmod>2026-06-19T21:04:43.523Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/gruff-llm-pronoun-fidelity-reasoning-and-biases-in-german--arxiv-2605.30214/</loc><lastmod>2026-06-19T01:51:36.431Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/meta-cognitive-memory-policy-optimization-for-long-horizon-llm-agents--arxiv-2605.30159/</loc><lastmod>2026-06-19T02:41:38.416Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/seal-can-saturated-benchmarks-be-revived-by-llm-as-a-meta-judge--arxiv-2605.30104/</loc><lastmod>2026-06-19T11:53:00.791Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/when-cloud-agents-meet-device-agents-lessons-from-hybrid-multi-agent-systems--arxiv-2605.30102/</loc><lastmod>2026-06-18T23:01:32.307Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/gamma-world-generative-multi-agent-world-modeling-beyond-two-players--arxiv-2605.28816/</loc><lastmod>2026-06-19T01:14:19.459Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/omniverifier-m1-multimodal-meta-verifier-with-explicit-structured-recalibration--arxiv-2605.28805/</loc><lastmod>2026-06-19T10:17:50.369Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/memtrace-tracing-and-attributing-errors-in-large-language-model-memory-systems--arxiv-2605.28732/</loc><lastmod>2026-06-19T21:02:30.270Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/joint-training-of-multi-token-prediction-in-reinforcement-learning-via-optimal-c--arxiv-2605.28184/</loc><lastmod>2026-06-19T21:15:05.820Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/sia-self-improving-ai-with-harness-weight-updates--arxiv-2605.27276/</loc><lastmod>2026-06-19T21:09:30.940Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/quack-questioning-understanding-and-auditing-communicated-knowledge-in-multimoda--arxiv-2605.27068/</loc><lastmod>2026-06-19T21:14:14.334Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/balancing-fidelity-and-diversity-in-diffusion-models-via-symmetric-attention-dec--arxiv-2605.27476/</loc><lastmod>2026-06-19T21:13:26.341Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/from-model-scaling-to-system-scaling-scaling-the-harness-in-agentic-ai--arxiv-2605.26112/</loc><lastmod>2026-06-18T04:16:45.036Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/squeezing-capacity-from-multimodal-large-language-models-for-subject-driven-gene--arxiv-2605.26111/</loc><lastmod>2026-06-19T19:28:15.809Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/when-gradients-collide-failure-modes-of-multi-objective-prompt-optimization-for--arxiv-2605.26046/</loc><lastmod>2026-06-19T21:15:25.315Z</lastmod></url>
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  <url><loc>https://www.opentrain.ai/papers/anticipate-and-learn-unleashing-idle-time-compute-in-proactive-agents--arxiv-2605.25971/</loc><lastmod>2026-06-19T03:31:58.530Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/triplet-block-diffusion-rwkv--arxiv-2605.25969/</loc><lastmod>2026-06-19T21:11:10.992Z</lastmod></url>
  <url><loc>https://www.opentrain.ai/papers/agenthijack-benchmarking-computer-use-agent-robustness-to-common-environment-cor--arxiv-2605.25707/</loc><lastmod>2026-06-19T12:46:52.628Z</lastmod></url>
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