Large language models (LLMs) are advancing in multimodal understanding and reasoning, accelerating medical model development. Traditional Chinese medicine (TCM) uses evidence from the four examinations to determine disease location and nature, differentiate syndromes and guide treatment. This diagnostic process constit...
Jia-Hang Xie, Tong Jin, Ling-Fei Wu et al.· 0 citations
VideoJev, a family of models that cast video understanding and interaction as structured decision tasks, is introduced, a family of models that cast video understanding and interaction as structured decision tasks that combine the semantic flexibility of MLLMs with efficient decisions that agents can use directly.
Yu-Han Zhu, Xiang-Yun Zeng, Qing-Yi Si et al.· 1 citation
This work compositions existing eviction methods across Transformer layers and systematically exploring the resulting layer-wise design space establish layer-wise method composition as an exploitable, placement-sensitive design dimension for KV cache compression.
Chao Fei, Kai-Huan Liang, Han-Zhi Hu et al.· 1 citation
EvoRS is introduced, a self-evolving RL framework that evolves the reward system from on-policy experience, representing it as an executable Reward-DAG, and is updated from on-policy rollouts and reward traces to maintain train-time reliability.
Wei-Yuan Li, Ai-Li Chen, Xin-Tao Wang et al.· 1 citation
This work proposes SocialRL, a multi-turn reinforcement learning framework using PPO that propagates delayed outcome rewards back to each turn, enabling long-horizon planning and demonstrates the effectiveness of SocialRL across synthetic and real social scenes, as well as standard and challenging social scenarios.
Jia-Ning Wang, Xin-Tao Wang, Ai-Li Chen et al.· 1 citation
The proposed FLY-EVAL++ is an evidence-driven evaluation protocol that combines deterministic verification of protocol compliance, physical feasibility, and safety constraints with fixed rubric-guided aggregation into interpretable multi-dimensional scores.
Ya-Lun Wu, Jun-Feng Fang, Jia-Wei Wang et al.· 0 citations
This work presents FORGE (Fabricated Orchestrated Reasoning chain for aGent Exploitation), a two-level attack that combines intra-document reasoning fabrication with inter-document chain coordination to hijack subtask planning.
Yu-Ru Pan, Ziheng Zhang, Junxiang Lei et al.· arXiv.org· 1 citation
Results show that EMAS can turn experience from new samples into reusable updates to MAS topology and prompts, and is best or tied in six of eight model--benchmark settings.
Chao Fei, Qing-Yi Si, Kai-Huan Liang et al.· 0 citations
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