https://www.opentrain.ai/papers/fedllm-bench-realistic-benchmarks-for-federated-learning-of-large-language-model--arxiv-2406.04845/2026-06-18T15:06:30.438Z https://www.opentrain.ai/papers/what-matters-in-transformers-not-all-attention-is-needed--arxiv-2406.15786/2026-06-18T14:57:58.427Z https://www.opentrain.ai/papers/user-story-tutor-ust-to-support-agile-software-developers--arxiv-2406.16259/2026-06-18T14:35:32.822Z https://www.opentrain.ai/papers/depth-anything-v2--arxiv-2406.09414/2026-06-18T14:19:00.607Z https://www.opentrain.ai/papers/bsrbf-kan-a-combination-of-b-splines-and-radial-basis-functions-in-kolmogorov-ar--arxiv-2406.11173/2026-06-18T13:17:37.771Z https://www.opentrain.ai/papers/mamba-yolo-a-simple-baseline-for-object-detection-with-state-space-model--arxiv-2406.05835/2026-06-18T13:16:44.435Z https://www.opentrain.ai/papers/facepsy-an-open-source-affective-mobile-sensing-system-analyzing-facial-behavior--arxiv-2406.17181/2026-06-18T13:04:13.264Z 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https://www.opentrain.ai/papers/gomaa-geo-goal-modality-agnostic-active-geo-localization--arxiv-2406.01917/2026-06-18T08:02:45.472Z https://www.opentrain.ai/papers/pcc-tuning-breaking-the-contrastive-learning-ceiling-in-semantic-textual-similar--arxiv-2406.09790/2026-06-18T08:02:45.268Z https://www.opentrain.ai/papers/multi-style-neural-radiance-field-with-adain--arxiv-2406.04960/2026-06-18T08:02:43.486Z https://www.opentrain.ai/papers/graspness-discovery-in-clutters-for-fast-and-accurate-grasp-detection--arxiv-2406.11142/2026-06-18T08:02:43.332Z https://www.opentrain.ai/papers/lighting-every-darkness-with-3dgs-fast-training-and-real-time-rendering-for-hdr--arxiv-2406.06216/2026-06-18T08:02:22.253Z https://www.opentrain.ai/papers/audiolcm-text-to-audio-generation-with-latent-consistency-models--arxiv-2406.00356/2026-06-18T08:02:20.592Z https://www.opentrain.ai/papers/multistability-of-small-zero-one-reaction-networks--arxiv-2406.11586/2026-06-18T08:01:27.786Z 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https://www.opentrain.ai/papers/segment-any-text-a-universal-approach-for-robust-efficient-and-adaptable-sentenc--arxiv-2406.16678/2026-06-18T07:58:38.743Z https://www.opentrain.ai/papers/itermask2-iterative-unsupervised-anomaly-segmentation-via-spatial-and-frequency--arxiv-2406.02422/2026-06-18T07:57:07.176Z https://www.opentrain.ai/papers/pyramidkv-dynamic-kv-cache-compression-based-on-pyramidal-information-funneling--arxiv-2406.02069/2026-06-18T07:57:04.777Z https://www.opentrain.ai/papers/scaling-up-masked-audio-encoder-learning-for-general-audio-classification--arxiv-2406.06992/2026-06-18T07:56:47.537Z https://www.opentrain.ai/papers/mvgamba-unify-3d-content-generation-as-state-space-sequence-modeling--arxiv-2406.06367/2026-06-18T07:56:42.924Z https://www.opentrain.ai/papers/a-new-branch-and-bound-pruning-framework-for-ell-0-regularized-problems--arxiv-2406.03504/2026-06-18T07:55:48.768Z https://www.opentrain.ai/papers/cross-language-soccer-framework-an-open-source-framework-for-the-robocup-2d-socc--arxiv-2406.05621/2026-06-18T07:55:48.489Z https://www.opentrain.ai/papers/crag-comprehensive-rag-benchmark--arxiv-2406.04744/2026-06-18T07:55:29.357Z https://www.opentrain.ai/papers/benchmarking-uncertainty-quantification-methods-for-large-language-models-with-l--arxiv-2406.15627/2026-06-18T07:55:21.907Z https://www.opentrain.ai/papers/autoregressive-image-generation-without-vector-quantization--arxiv-2406.11838/2026-06-18T07:54:22.908Z https://www.opentrain.ai/papers/muharaf-manuscripts-of-handwritten-arabic-dataset-for-cursive-text-recognition--arxiv-2406.09630/2026-06-17T23:43:22.457Z https://www.opentrain.ai/papers/pvuw-2024-challenge-on-complex-video-understanding-methods-and-results--arxiv-2406.17005/2026-06-17T23:08:26.941Z 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https://www.opentrain.ai/papers/toward-unified-practices-in-trajectory-prediction-research-on-bird-s-eye-view-da--arxiv-2405.00604/2026-06-20T05:52:43.324Z https://www.opentrain.ai/papers/clibd-bridging-vision-and-genomics-for-biodiversity-monitoring-at-scale--arxiv-2405.17537/2026-06-20T01:33:54.606Z https://www.opentrain.ai/papers/balance-reward-and-safety-optimization-for-safe-reinforcement-learning-a-perspec--arxiv-2405.01677/2026-06-19T18:54:49.038Z https://www.opentrain.ai/papers/optimizing-large-language-models-for-openapi-code-completion--arxiv-2405.15729/2026-06-19T16:23:33.077Z https://www.opentrain.ai/papers/refchecker-reference-based-fine-grained-hallucination-checker-and-benchmark-for--arxiv-2405.14486/2026-06-19T16:19:33.246Z https://www.opentrain.ai/papers/transformers-are-ssms-generalized-models-and-efficient-algorithms-through-struct--arxiv-2405.21060/2026-06-19T15:43:31.018Z 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