3 papers indexed
Yuan Guo, Yilong Chen, Chao Hu, Xianghao Yu, Liang Hong, Jie Xu
Large language model (LLM) agents have shown growing capabilities in tool use, code execution, artifact inspection, and iterative revision, creating new opportunities for automating scientific research. To the best of our knowledge, this paper presents the first end-to-end autore…
Liming Liu, Chao Hu, Mingfei Lu, Yiwei Ge, Xingle Li, Heyuan Shi
Graph-based fraud detection is essential for safeguarding large-scale transaction systems, where undetected anomalies may lead to substantial financial losses and security risks. Real-world fraud graphs pose two coupled challenges: sparse and imbalanced supervision, where verifie…
Wenhao Zeng, Yuling Shi, Xiaodong Gu, Chao Hu, Chaofan Wang, Yuhao Cui, et al.
Program verifiers play a central role in training coding agents, including selecting trajectories for supervised fine-tuning (SFT) and providing rewards for reinforcement learning (RL). Standard execution-based verification requires running unit tests inside per-repository enviro…