5 papers
AutoRedClaw: Automated Red-Teaming for Claw-Style Agents
Hao Li, Tongyan Hu, Weidi Luo +8
Agent systems are shifting from task-scoped tool-use agents to persistent, personalized assistants such as OpenClaw. These claw-style agents maintain configuration files (e.g., AGE…
Gradually Compacting Large Language Models for Reasoning Like a Boiling Frog
Yiran Zhao, Shengyang Zhou, Zijian Wu +7
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, but their substantial size often demands significant computational resources. To reduce resource c…
FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in Finance Domain
Tiansheng Hu, Tongyan Hu, Liuyang Bai +3
Recent LLMs have demonstrated promising ability in solving finance related problems. However, applying LLMs in real-world finance application remains challenging due to its high ri…
VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC Videos
Tingyu Song, Tongyan Hu, Guo Gan +1
MLLMs have been widely studied for video question answering recently. However, most existing assessments focus on natural videos, overlooking synthetic videos, such as AI-generated…
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Yilun Zhao, Lujing Xie, Haowei Zhang +16
We introduce MMVU, a comprehensive expert-level, multi-discipline benchmark for evaluating foundation models in video understanding. MMVU includes 3,000 expert-annotated questions…