Author

Ruixue Ding

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#natural language process... Preprint Sep 2026

ArenaFlow: From Trajectory Ranking to Hierarchical Credit Propagation for Open-Ended Agent RL

Reinforcement learning has substantially improved large language model (LLM) agents in verifiable domains, but remains difficult to apply to open-ended agent tasks, where solutions are diverse and reliable scalar rewards are hard to obtain. Recent pairwise evaluation methods alleviate reward discrimination collapse by...

Qiang Zhang, Rui-Xue Ding, Fanrui Zhang et al. · 1 citation

#artificial intelligence Preprint Sep 2026

ARISE-RL: Agentic Rubric-Grounded Iterative Self-Evolution with Reinforcement Learning

ARISE-RL, a novel full-cycle self-evolution framework that couples a task/rubric Generator and a reasoning Solver through rubric-mediated co-evolution, is proposed and ECR-Bench, an expert-calibrated rubric benchmark suite covering single-tool deep research and multi-tool travel planning is presented.

Fanrui Zhang, Rui-Xue Ding, Qiang Zhang et al. · 0 citations

Jul 2026

SecRespond: Benchmarking AI Agents for Real-World Post-Compromise Incident Response

Experimental results show that although current agents can reliably uncover the problems exposed by alerts, they struggle to proactively investigate the disk for silent intrusions and to produce comprehensive, verified remediation plans, with no model achieving complete detection and remediation on any single range.

Le-Han Wang, Boli Chen, Ruixue Ding et al. · arXiv.org · 0 citations