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Generative Skill Composition for LLM Agents
Xinyu Zhao, Zhen Tan, Vaishnav Tadiparthi +5
Recent LLM agents benefit from skills for solving complex tasks. Skills encapsulate modular packages of procedural knowledge and instructions for performing specialized tasks, such…
Does AI Reviewer See the Full Picture? Attacking and Defending Multimodal Peer Review
Xinyu Zhao, Rana Muhammad Shahroz Khan, Zhen Xu +2
The integration of Large Language Models (LLMs) and Multimodal LLMs (MLLMs) into scientific peer-review workflows introduces novel and significant risks for adversarial manipulatio…
Transferring Expert Cognitive Models to Social Robots via Agentic Concept Bottleneck Models
Xinyu Zhao, Zhen Tan, Maya Enisman +4
Successful group meetings, such as those implemented in group behavioral-change programs, work meetings, and other social contexts, must promote individual goal setting and executi…
GuideLLM: Exploring LLM-Guided Conversation with Applications in Autobiography Interviewing
Jinhao Duan, Xinyu Zhao, Zhuoxuan Zhang +12
Although Large Language Models (LLMs) succeed in human-guided conversations such as instruction following and question answering, the potential of LLM-guided conversations-where LL…
Dialogue is Better Than Monologue: Instructing Medical LLMs via Strategical Conversations
Zijie Liu, Xinyu Zhao, Jie Peng +5
Current medical AI systems often fail to replicate real-world clinical reasoning, as they are predominantly trained and evaluated on static text and question-answer tasks. These tu…
SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH)
Bernardo Consoli, Xizhi Wu, Song Wang +10
Extracting social determinants of health (SDoH) from unstructured medical notes depends heavily on labor-intensive annotations, which are typically task-specific, hampering reusabi…