7 citations · 11 across the 12 of their papers we have counts for
6 papers · 1 filter
EMCompress: Video-LLMs with Endomorphic Multimodal Compression
Zheyu Fan, Jiateng Liu, Yuji Zhang +4
Video-LLMs face a fundamental tension in long-video reasoning: static, sparse frame sampling either dilutes evidence across task-irrelevant segments at significant cost or misses f…
Atomic Reasoning for Scientific Table Claim Verification
Yuji Zhang, Qingyun Wang, Cheng Qian +7
Scientific texts often convey authority due to their technical language and complex data. However, this complexity can sometimes lead to the spread of misinformation. Non-experts a…
ModelingAgent: Bridging LLMs and Mathematical Modeling for Real-World Challenges
Cheng Qian, Hongyi Du, Hongru Wang +6
Recent progress in large language models (LLMs) has enabled substantial advances in solving mathematical problems. However, existing benchmarks often fail to reflect the complexity…
TAMA: A Human-AI Collaborative Thematic Analysis Framework Using Multi-Agent LLMs for Clinical Interviews
Huimin Xu, Seungjun Yi, Terence Lim +9
Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable insights in healthcare but is resource-i…
The Law of Knowledge Overshadowing: Towards Understanding, Predicting, and Preventing LLM Hallucination
Yuji Zhang, Sha Li, Cheng Qian +8
Hallucination is a persistent challenge in large language models (LLMs), where even with rigorous quality control, models often generate distorted facts. This paradox, in which err…
SafeSwitch: Steering Unsafe LLM Behavior via Internal Activation Signals
Peixuan Han, Cheng Qian, Xiusi Chen +3
Large language models (LLMs) exhibit exceptional capabilities across various tasks but also pose risks by generating harmful content. Existing safety mechanisms, while improving mo…