3 papers
cs.MA2026
Helix: A Dual-Helix Co-Evolutionary Multi-Agent System for Prompt Optimization and Question Reformulation
Kewen Zhu, Liping Yi, Zhiming Zhao +2
Automated prompt optimization (APO) aims to improve large language model performance by refining prompt instructions. However, existing methods are largely constrained by fixed pro…
cs.AI2025
SpeakRL: Synergizing Reasoning, Speaking, and Acting in Language Models with Reinforcement Learning
Emre Can Acikgoz, Jinoh Oh, Jie Hao +7
Effective human-agent collaboration is increasingly prevalent in real-world applications. Current trends in such collaborations are predominantly unidirectional, with users providi…
cs.AI2025
MAC: A Multi-Agent Framework for Interactive User Clarification in Multi-turn Conversations
Emre Can Acikgoz, Jinoh Oh, Joo Hyuk Jeon +7
Conversational agents often encounter ambiguous user requests, requiring an effective clarification to successfully complete tasks. While recent advancements in real-world applicat…