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20232026
most citedAssessment of Multimodal Large Language Models in Alignment with Human Values

2 citations · 7 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control

Lihao Sun, Lewen Yan, Xiaoya Lu +3

We show that emotion vectors in LLMs are organized by a two-dimensional valence-arousal (VA) subspace exhibiting circular geometry. Through principal component decomposition and ri…

cs.CL20241 cited

The Better Angels of Machine Personality: How Personality Relates to LLM Safety

Jie Zhang, Dongrui Liu, Chen Qian +4

Personality psychologists have analyzed the relationship between personality and safety behaviors in human society. Although Large Language Models (LLMs) demonstrate personality tr…

cs.CL20241 cited

Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey

Zhichen Dong, Zhanhui Zhou, Chao Yang +2

Large Language Models (LLMs) are now commonplace in conversation applications. However, their risks of misuse for generating harmful responses have raised serious societal concerns…

cs.CL2024

CodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion

Qibing Ren, Chang Gao, Jing Shao +4

The rapid advancement of Large Language Models (LLMs) has brought about remarkable generative capabilities but also raised concerns about their potential misuse. While strategies l…

cs.CL2024

Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models

Chen Qian, Jie Zhang, Wei Yao +5

Ensuring the trustworthiness of large language models (LLMs) is crucial. Most studies concentrate on fully pre-trained LLMs to better understand and improve LLMs' trustworthiness.…