4 papers
CARO: Chain-of-Analogy Reasoning Optimization for Robust Content Moderation
Bingzhe Wu, Haotian Lu, Yuchen Mou
Current large language models (LLMs), even those explicitly trained for reasoning, often struggle with ambiguous content moderation cases due to misleading "decision shortcuts" emb…
CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMs
Haotian Lu, Yuchen Mou, Bingzhe Wu
Content moderation in online platforms faces persistent challenges due to the evolving complexity of user-generated content and the limitations of traditional rule-based and machin…
ICAT: Incident-Case-Grounded Adaptive Testing for Physical-Risk Prediction in Embodied World Models
Zhenglin Lai, Sirui Huang, Yuteng Li +3
Video-generative world models are increasingly used as neural simulators for embodied planning and policy learning, yet their ability to predict physical risk and severe consequenc…
EARBench: Towards Evaluating Physical Risk Awareness for Task Planning of Foundation Model-based Embodied AI Agents
Zihao Zhu, Bingzhe Wu, Zhengyou Zhang +3
Embodied artificial intelligence (EAI) integrates advanced AI models into physical entities for real-world interaction. The emergence of foundation models as the "brain" of EAI age…