most citedReasoning through Exploration: A Reinforcement Learning Framework for Robust Function Calling

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cs.AI2026

Design the Feedback, Not Just the Reward: Environments for Open-Ended Reinforcement Learning

Rui Jin, Jikai Chen, Yihan Chen +7

Reinforcement learning has advanced large language models on tasks with reliable verifiers, where checking an outcome provides a clear basis for reward. Extending this approach to…

cs.AI2026

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…

cs.AI2025

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.…

cs.AI2025

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…

cs.AI2025

SQLCritic: Correcting Text-to-SQL Generation via Clause-wise Critic

Jikai Chen, Leilei Gan, Ziyu Zhao +3

Existing refinement methods in LLM-based Text-to-SQL systems exhibit limited effectiveness. They often introduce new errors during the self-correction process and fail to detect an…