8 papers · 1 filter
Think Big, Search Small: Where Capacity Matters in Hierarchical Search Agents?
Qinnan Cai, Yibo Zhao, Xiang Li
Large language model based search agents increasingly adopt multi-agent architectures in which a main agent decomposes a complex question into sub-queries and dispatches them to pa…
Skill is Not One-Size-Fits-All: Model-Aware Skill Alignment for LLM Agents
Jianxiang Yu, Jiapeng Zhu, Bochen Lin +3
LLM agents increasingly retrieve externally curated skills-procedural instructions retrieved at decision time-to improve performance on long-horizon interactive tasks. Existing ski…
Retrieval, Reward, and Training Protocols: What Matters in Training Search Agents?
Yibo Zhao, Zichen Ding, Jiayi Wu +2
Search agents powered by large language models can autonomously decompose queries, retrieve information, and synthesize answers through multi-step reasoning. However, the rapid gro…
Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning
Jiapeng Zhu, Jianxiang Yu, Yibo Zhao +5
Equipping large language models with explicit skills has emerged as a promising paradigm for enabling autonomous agents to solve complex tasks. Agent skills can be inherently divid…
Beyond Chunk-Local Extraction: Cross-Chunk Graph Augmentation for GraphRAG
Jiaming Zhang, Yibo Zhao, Jing Yu +2
GraphRAG extends retrieval-augmented generation by organizing corpora as explicit knowledge graphs, enabling graph-based retrieval for complex question answering. However, existing…
MERIT: Matching Expertise via Rubric-Informed Training for Reviewer Assignment
Zixuan Yang, Yibo Zhao, Weicong Liu +1
Matching submissions with suitable reviewers at scale is a growing challenge for major venues, yet existing approaches either rely on coarse proxy signals that conflate general rel…