1 citations · 1 across the 6 of their papers we have counts for
7 papers
Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference
Anna Hart, Chi Han, Jeonghwan Kim +2
Modern Protein Language Models (PLMs) apply transformer-based model architectures from natural language processing to biological sequences, predicting a variety of protein function…
Neural Synchrony Between Socially Interacting Language Models
Zhining Zhang, Wentao Zhu, Chi Han +2
Neuroscience has uncovered a fundamental mechanism of our social nature: human brain activity becomes synchronized with others in many social contexts involving interaction. Tradit…
ReIn: Conversational Error Recovery with Reasoning Inception
Takyoung Kim, Jinseok Nam, Chandrayee Basu +5
Conversational agents powered by large language models (LLMs) with tool integration achieve strong performance on fixed task-oriented dialogue datasets but remain vulnerable to una…
Towards Agentic Intelligence for Materials Science
Huan Zhang, Yizhan Li, Wenhao Huang +18
The convergence of artificial intelligence and materials science presents a transformative opportunity, but achieving true acceleration in discovery requires moving beyond task-iso…
Toward Cognitive Supersensing in Multimodal Large Language Model
Boyi Li, Yifan Shen, Yuanzhe Liu +12
Multimodal Large Language Models (MLLMs) have achieved remarkable success in open-vocabulary perceptual tasks, yet their ability to solve complex cognitive problems remains limited…
That's Deprecated! Understanding, Detecting, and Steering Knowledge Conflicts in Language Models for Code Generation
Jaesung Bae, Cameron Churchwell, Mitchell Hermon +5
This paper investigates how large language models (LLMs) behave when faced with discrepancies between their parametric knowledge and conflicting information contained in a prompt.…
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…