3 papers
cs.AI2026
Emotion2Skill: Model-Internal Emotion Signals for Adaptive Skill Selection and Evolution
Bohan Lin, Hejia Geng, Xinyi Xie +5
Skill-based LLM agents select reusable procedures from an external library to solve complex tasks, yet their routing decisions rely entirely on text-level signals such as task desc…
cs.CL2026
What Should a Skill Remember? Quality--Cost Trade-offs in Cost-Aware Skill Rewriting for Language Model Agents
Qinghua Xing, Yinda Chen, Yaping Jin +6
Large language model agents increasingly rely on skills: reusable procedural documents encoding workflows, tool use, implementation patterns, validation checks, and domain rules. S…
cs.SE2025
Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks
Kang Yang, Xinjun Mao, Shangwen Wang +7
Pre-trained code models rely heavily on high-quality pre-training data, particularly human-written reference comments that bridge code and natural language. However, these comments…