3 papers
cs.CL2026
Swarm Skills: A Portable, Self-Evolving Multi-Agent System Specification for Coordination Engineering
Xinyu Zhang, Zhicheng Dou, Deyang Li +10
As artificial intelligence engineering paradigms shift from single-agent Prompt and Context Engineering toward multi-agent \textbf{Coordination Engineering}, the ability to codify…
cs.AI2026
Process In-Context Learning: Enhancing Mathematical Reasoning via Dynamic Demonstration Insertion
Ang Gao, Changshuo Zhang, Xiao Zhang +4
In-context learning (ICL) has proven highly effective across diverse large language model (LLM) tasks. However, its potential for enhancing tasks that demand step-by-step logical d…
cs.CL2025
Revisiting Chain-of-Thought Prompting: Zero-shot Can Be Stronger than Few-shot
Xiang Cheng, Chengyan Pan, Minjun Zhao +5
In-Context Learning (ICL) is an essential emergent ability of Large Language Models (LLMs), and recent studies introduce Chain-of-Thought (CoT) to exemplars of ICL to enhance the r…