3 papers
cs.AI2026
SkillDAG: Self-Evolving Typed Skill Graphs for LLM Skill Selection at Scale
Tong Bai, Zhenglin Wan, Pengfei Zhou +3
As LLM agents adopt large skill libraries, selecting the right subset becomes a structural problem rather than a similarity-matching one: skills depend on, conflict with, specializ…
cs.SE2026
Towards Iterative End-to-End Software Development: A Feature-Driven Multi-Agent Framework
Junwei Liu, Chen Xu, Chong Wang +5
Recent advances in large language model agents offer the promise of automating end-to-end software development from natural language requirements. However, existing approaches larg…
cs.CL2026
Unlocking the Black Box of Latent Reasoning: An Interpretability-Guided Approach to Intervention
Shuochen Chang, Tong Bai, Xiaofeng Zhang +5
Latent reasoning enables Large Language Models (LLMs) to perform multi-step inference within continuous hidden states, offering efficiency gains over explicit Chain-of-Thought (CoT…