13 papers
Skills Know Their Neighbors: Cluster-Contrastive Capability Pages for Skill Retrieval
Zifei Wang, Wei Wen, Qiang Ji +1
As skill libraries grow, large language model agents must retrieve reusable skills from candidates that often share the same topic and vocabulary but implement different capabiliti…
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…
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…
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…
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…
Toward Native Multimodal Modeling: A Roadmap
Siyu An, Junru Lu, Junnan Dong +18
Multimodal modeling represents a vital step from modality-agnostic reasoning toward world modeling. While early approaches predominantly rely on late-fusion that assembles encoders…