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20232026
most citedBeyond One-Preference-Fits-All Alignment: Multi-Objective Direct Preference Optimization

3 citations · 13 across the 12 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.CL2024★ 1 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.CL2024★ 1 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.…