most citedUnderstanding Language Prior of LVLMs by Contrasting Chain-of-Embedding

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cs.CL2026

SensorPersona: An LLM-Empowered System for Continual Persona Extraction from Longitudinal Mobile Sensor Streams

Bufang Yang, Lilin Xu, Yixuan Li +3

Personalization is essential for Large Language Model (LLM)-based agents to adapt to users' preferences and improve response quality and task performance. However, most existing ap…

cs.CL2025

Cognition-of-Thought Elicits Social-Aligned Reasoning in Large Language Models

Xuanming Zhang, Yuxuan Chen, Samuel Yeh +1

Large language models (LLMs) excel at complex reasoning but can still exhibit harmful behaviors. Current alignment strategies typically embed safety into model weights, making thes…

cs.CL2025

LH-Deception: Simulating and Understanding LLM Deceptive Behaviors in Long-Horizon Interactions

Yang Xu, Xuanming Zhang, Samuel Yeh +4

Deception is a pervasive feature of human communication and an emerging concern in large language models (LLMs). While recent studies document instances of LLM deception, most eval…

cs.CL2025

LUMINA: Detecting Hallucinations in RAG System with Context-Knowledge Signals

Samuel Yeh, Sharon Li, Tanwi Mallick

Retrieval-Augmented Generation (RAG) aims to mitigate hallucinations in large language models (LLMs) by grounding responses in retrieved documents. Yet, RAG-based LLMs still halluc…

cs.CL2025

MetaMind: Modeling Human Social Thoughts with Metacognitive Multi-Agent Systems

Xuanming Zhang, Yuxuan Chen, Samuel Yeh +1

Human social interactions depend on the ability to infer others' unspoken intentions, emotions, and beliefs-a cognitive skill grounded in the psychological concept of Theory of Min…

cs.CL2025

HalluEntity: Benchmarking and Understanding Entity-Level Hallucination Detection

Min-Hsuan Yeh, Max Kamachee, Seongheon Park +1

To mitigate the impact of hallucination nature of LLMs, many studies propose detecting hallucinated generation through uncertainty estimation. However, these approaches predominant…