69 citations · 123 across the 9 of their papers we have counts for
9 papers
Conversation as Measurement in Clinical Encounters: Observable Phase Structure, Partially Observable Patient State
Lily Chen, Ted Mau, Michael Gensheimer +3
Many modern AI systems analyze conversational traces to infer aspects of human interaction and state, implicitly assuming that such information is recoverable from conversation. We…
Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment
Sheng Liu, Long Chen, Zeyun Zhao +16
Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in multimodal foundation models have…
More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models
Chengzhi Liu, Zhongxing Xu, Qingyue Wei +5
Test-time compute has empowered multimodal large language models to generate extended reasoning chains, yielding strong performance on tasks such as multimodal math reasoning. Howe…
Knowledge or Reasoning? A Close Look at How LLMs Think Across Domains
Juncheng Wu, Sheng Liu, Haoqin Tu +5
Recent advances in reasoning-enhanced Large Language Models such as OpenAI-o1/3 and DeepSeek-R1 have significantly improved performance on complex tasks. However, the quality and t…
Reducing Hallucinations in Vision-Language Models via Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing +1
Hallucination poses a challenge to the deployment of large vision-language models (LVLMs) in applications. Unlike in large language models (LLMs), hallucination in LVLMs often aris…
Automated radiotherapy treatment planning guided by GPT-4Vision
Sheng Liu, Oscar Pastor-Serrano, Yizheng Chen +10
Objective: Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires the iterative adjustment of model parameters to balance multiple con…
Mapping the Increasing Use of LLMs in Scientific Papers
Weixin Liang, Yaohui Zhang, Zhengxuan Wu +11
Scientific publishing lays the foundation of science by disseminating research findings, fostering collaboration, encouraging reproducibility, and ensuring that scientific knowledg…
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews
Weixin Liang, Zachary Izzo, Yaohui Zhang +9
We present an approach for estimating the fraction of text in a large corpus which is likely to be substantially modified or produced by a large language model (LLM). Our maximum l…
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing +1
Large language models (LLMs) demonstrate emergent in-context learning capabilities, where they adapt to new tasks based on example demonstrations. However, in-context learning has…