activity
20222026
most citedMetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

153 citations · 192 across the 14 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CL2025

VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations

Yupeng Xie, Zhiyang Zhang, Yifan Wu +8

Visualization, a domain-specific yet widely used form of imagery, is an effective way to turn complex datasets into intuitive insights, and its value depends on whether data are fa…

cs.CL2025

Improving Context Fidelity via Native Retrieval-Augmented Reasoning

Suyuchen Wang, Jinlin Wang, Xinyu Wang +6

Large language models (LLMs) often struggle with context fidelity, producing inconsistent answers when responding to questions based on provided information. Existing approaches ei…

cs.SE2025★ 1 cited

You Don't Know Until You Click:Automated GUI Testing for Production-Ready Software Evaluation

Yutong Bian, Xianhao Lin, Yupeng Xie +11

Large Language Models (LLMs) and code agents in software development are rapidly evolving from generating isolated code snippets to producing full-fledged software applications wit…

cs.CL2025

Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

Xiangru Tang, Tianrui Qin, Tianhao Peng +15

AI agent frameworks operate in isolation, forcing agents to rediscover solutions and repeat mistakes across different systems. Despite valuable problem-solving experiences accumula…

cs.AI2025★ 16 cited

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Bang Liu, Xinfeng Li, Jiayi Zhang +45

The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated…

cs.CL2025★ 2 cited

Self-Supervised Prompt Optimization

Jinyu Xiang, Jiayi Zhang, Zhaoyang Yu +8

Well-designed prompts are crucial for enhancing Large language models' (LLMs) reasoning capabilities while aligning their outputs with task requirements across diverse domains. How…