9 papers · 1 filter
LiveAgentBench: Comprehensive Benchmarking of Agentic Systems Across 104 Real-World Challenges
Hao Li, Huan Wang, Jinjie Gu +3
As large language models grow more capable, general AI agents have become increasingly prevalent in practical applications. However, existing benchmarks face significant limitation…
Don't Just Fine-tune the Agent, Tune the Environment
Siyuan Lu, Zechuan Wang, Hongxuan Zhang +5
Large Language Model (LLM) agents show great promise for complex, multi-turn tool-use tasks, but their development is often hampered by the extreme scarcity of high-quality trainin…
V2P: Visual Attention Calibration for GUI Grounding via Background Suppression and Center Peaking
Jikai Chen, Long Chen, Dong Wang +6
Precise localization of GUI elements is crucial for the development of GUI agents. Traditional methods rely on bounding box or center-point regression, neglecting spatial interacti…
V2P: Visual Attention Calibration for GUI Grounding via Background Suppression and Center Peaking
Jikai Chen, Long Chen, Dong Wang +6
Precise localization of GUI elements is crucial for the development of GUI agents. Traditional methods rely on bounding box or center-point regression, neglecting spatial interacti…
FunReason-MT Technical Report: Advanced Data Synthesis Solution for Real-world Multi-Turn Tool-use
Zengzhuang Xu, Bingguang Hao, Zechuan Wang +14
Function calling (FC) empowers large language models (LLMs) and autonomous agents to interface with external tools, a critical capability for solving complex, real-world problems.…
Recon-Act: A Self-Evolving Multi-Agent Browser-Use System via Web Reconnaissance, Tool Generation, and Task Execution
Kaiwen He, Zhiwei Wang, Chenyi Zhuang +1
Recent years, multimodal models have made remarkable strides and pave the way for intelligent browser use agents. However, when solving tasks on real world webpages in multi-turn,…