9 citations · 34 across the 50 of their papers we have counts for
12 papers · 1 filter
From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents
Haipeng Ding, Yuexiang Xie, Zhewei Wei +2
Tool utilization enables Large Language Model (LLM) agents to interact with the real world and resolve complex tasks. However, existing agent frameworks predominantly rely on stati…
CDR-Bench: Evaluating Faithful Execution of Compositional, Order-Sensitive Data Refinement Recipes
Yuchen Huang, Xiang Li, Zhenqing Ling +5
Data refinement involves executing multi-step recipes over evolving text states, where both composition and execution order of processing operators determine the outcome. While exi…
Beyond Domains: Reusing Web Skills via Transferable Interaction Patterns
Shiqi He, Yue Cui, Feijie Wu +5
Large language model (LLM) web agents are usually deployed as tool callers: each turn, the model reads a fresh page observation and emits one structured tool action. When every act…
Enhancing Multimodal Retrieval via Complementary Information Extraction and Alignment
Delong Zeng, Yuexiang Xie, Yaliang Li +1
Multimodal retrieval has emerged as a promising yet challenging research direction in recent years. Most existing studies in multimodal retrieval focus on capturing information in…
BOTS: A Unified Framework for Bayesian Online Task Selection in LLM Reinforcement Finetuning
Qianli Shen, Daoyuan Chen, Yilun Huang +4
Reinforcement finetuning (RFT) is a key technique for aligning Large Language Models (LLMs) with human preferences and enhancing reasoning, yet its effectiveness is highly sensitiv…
Branch-and-Browse: Efficient and Controllable Web Exploration with Tree-Structured Reasoning and Action Memory
Shiqi He, Yue Cui, Xinyu Ma +3
Autonomous web agents powered by large language models (LLMs) show strong potential for performing goal-oriented tasks such as information retrieval, report generation, and online…