30 citations · 34 across the 12 of their papers we have counts for
4 papers · 1 filter
Agent^2 RL-Bench: Can LLM Agents Engineer Agentic RL Post-Training?
Wanyi Chen, Xiao Yang, Xu Yang +7
We introduce Agent2 RL-Bench, a compact diagnostic benchmark for evaluating agentic RL post-training, which tests whether LLM agents can autonomously design, implement, debug, and…
Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search
Yifei Zhang, Xu Yang, Xiao Yang +8
LLM-based agents for machine learning engineering (MLE) predominantly rely on tree search, a form of gradient-free optimization that uses scalar validation scores to rank candidate…
VidDoS: Universal Denial-of-Service Attack on Video-based Large Language Models
Duoxun Tang, Dasen Dai, Jiyao Wang +3
Video-LLMs are increasingly deployed in safety-critical applications but are vulnerable to Energy-Latency Attacks (ELAs) that exhaust computational resources. Current image-centric…
FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
Qizheng Li, Yifei Zhang, Xiao Yang +4
Fine-tuning large language models for vertical domains remains labor-intensive, requiring practitioners to curate data, configure training, and iteratively diagnose model behavior.…