collaborators

12 papers

cs.LG2026

Training-Free Hashing-Based Attention via Binary Principal Components

Daohai Yu, Zhanpeng Zeng, Keyu Chen +6

Long-context large language models (LLMs) are increasingly deployed in real-world applications, yet self-attention remains a major efficiency bottleneck -- especially during decodi…

cs.IR2026

Skill Is Not Document: Query-Conditioned Compatibility for LLM Agent Skill Routing

Zifei Wang, Wei Wen, Qiang Ji +3

Large language model agents increasingly rely on reusable skills, making skill retrieval a critical front-end component of agent systems. Skill retrieval, however, is not ordinary…

cs.LG2026

RSPO: Reward-Swap Policy Optimization for Multi-Turn LLM Agents

Qiang Liu, Taian Guo, Ruizhi Qiao +1

Reinforcement learning holds significant potential for training large language models (LLMs) to handle multi-turn interactive tasks. However, in long-horizon, multi-turn tasks char…

cs.IR2026

Breaking the Evaluation Paradox: Evaluating High-Entropy Search with Computationally Irreducible Constraints

Juntao Wu, Wei Wen, Xianting Huang +4

Evaluating the exhaustive search capabilities of large language models (LLMs) is plagued by a fundamental paradox: verifying completeness requires complete ground truth, yet high-e…

cs.CV2026

Beyond Encoder Accumulation: Measuring Encoder Roles in Multi-Encoder VLMs

Wei Ding, Yudong Zhang, Ruobing Xie +3

As foundation models scale toward fusing more heterogeneous visual streams, understanding how diverse encoders interact under joint training becomes a prerequisite for principled d…

cs.CV2026

Moment-Video: Diagnosing Temporal Fidelity of Video MLLMs on Momentary Visual Events

Xiaolin Liu, Yilun Zhu, Xiangyu Zhao +9

Video multimodal large language models (MLLMs) have made rapid progress on general and long-form video understanding, yet their ability to preserve brief answer-critical visual evi…