5 papers
MT-OSC: Path for LLMs that Get Lost in Multi-Turn Conversation
Jyotika Singh, Fang Tu, Miguel Ballesteros +6
Large language models (LLMs) suffer significant performance degradation when user instructions and context are distributed over multiple conversational turns, yet multi-turn (MT) i…
Automated Composition of Agents: A Knapsack Approach for Agentic Component Selection
Michelle Yuan, Khushbu Pahwa, Shuaichen Chang +5
Designing effective agentic systems requires the seamless composition and integration of agents, tools, and models within dynamic and uncertain environments. Most existing methods…
MemInsight: Autonomous Memory Augmentation for LLM Agents
Rana Salama, Jason Cai, Michelle Yuan +4
Large language model (LLM) agents have evolved to intelligently process information, make decisions, and interact with users or tools. A key capability is the integration of long-t…
A Study on Leveraging Search and Self-Feedback for Agent Reasoning
Karthikeyan K, Michelle Yuan, Elman Mansimov +6
Recent works have demonstrated that incorporating search during inference can significantly improve reasoning capabilities of language agents. Some approaches may make use of the g…
Towards Effective GenAI Multi-Agent Collaboration: Design and Evaluation for Enterprise Applications
Raphael Shu, Nilaksh Das, Michelle Yuan +2
AI agents powered by large language models (LLMs) have shown strong capabilities in problem solving. Through combining many intelligent agents, multi-agent collaboration has emerge…