6 papers
Better, Faster, Stronger: Programmatic Skill Learning Best Reduces Agent Cost
Zixi Huang, Xiheng Wang, Andrew Wang +4
Recently, the practice of augmenting LLM agent capability with skills has gained prevalence. We explore the cost effective adaptation of agents to novel domains by means of learnin…
AgentCL: Toward Rigorous Evaluation of Continual Learning in Language Agents
Yiheng Shu, Bernal Jiménez Gutiérrez, Saisri Padmaja Jonnalagedda +3
Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future episodes. Continual learning…
REMem: Reasoning with Episodic Memory in Language Agent
Yiheng Shu, Saisri Padmaja Jonnalagedda, Xiang Gao +5
Humans excel at remembering concrete experiences along spatiotemporal contexts and performing reasoning across those events, i.e., the capacity for episodic memory. In contrast, me…
Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge
Boyu Gou, Zanming Huang, Yuting Ning +23
Agentic search such as Deep Research systems-where agents autonomously browse the web, synthesize information, and return comprehensive citation-backed answers-represents a major s…
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi +2
Our ability to continuously acquire, organize, and leverage knowledge is a key feature of human intelligence that AI systems must approximate to unlock their full potential. Given…
Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers
Shijie Chen, Bernal Jiménez Gutiérrez, Yu Su
Information retrieval (IR) systems have played a vital role in modern digital life and have cemented their continued usefulness in this new era of generative AI via retrieval-augme…