4 papers
AgentOmnia: Scaling Agentic Models for Full-Scenario Applications
Hao Jiang, Gangtao Xin, Yingdi Huang +35
Large language model agents have advanced rapidly, yet progress remains fragmented across domains, capabilities, task difficulty, and interaction settings. We frame this as full-sc…
Cross-Layer Misalignment Detection in Agent Skills: A Progressive Loading-Aware Contrastive Learning Approach
Chengjun Zhang, Yang Gao, Jianna Hur +2
Large language model (LLM) agents are increasingly extended through Agent Skills, reusable artifacts that package natural-language metadata, procedural instructions, and execution-…
Kimi-Dev: Agentless Training as Skill Prior for SWE-Agents
Zonghan Yang, Shengjie Wang, Kelin Fu +18
Large Language Models (LLMs) are increasingly applied to software engineering (SWE), with SWE-bench as a key benchmark. Solutions are split into SWE-Agent frameworks with multi-tur…
Learning to Plan Before Answering: Self-Teaching LLMs to Learn Abstract Plans for Problem Solving
Jin Zhang, Flood Sung, Zhilin Yang +2
In the field of large language model (LLM) post-training, the effectiveness of utilizing synthetic data generated by the LLM itself has been well-presented. However, a key question…