activity
20232026
most citedComprehensive Assessment of Toxicity in ChatGPT

5 citations · 11 across the 35 of their papers we have counts for

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34 papers · 1 filter

cs.CR2026

"Shut Up and Let Me Enjoy My Otome": Understanding and Measuring the Toxicity in Otome Game Communities

Yage Zhang, Xinyue Shen, Yukun Jiang +2

Otome games, a romance simulation genre primarily targeting female, have emerged as a major force in the global gaming market, attracting hundreds of millions of players and billio…

cs.CR2026

BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning

Ziqing Yang, Rui Wen, Xinlei He +3

Prompt learning is a new machine learning paradigm that has attracted ample attention due to its simplicity and proven efficacy. Despite its growing adoption, the security vulnerab…

cs.CR2026

HarmfulSkillBench: How Do Harmful Skills Weaponize Your Agents?

Yukun Jiang, Yage Zhang, Michael Backes +2

Large language models (LLMs) have evolved into autonomous agents that rely on open skill ecosystems (e.g., ClawHub and Skills.Rest), hosting numerous publicly reusable skills. Exis…

cs.CR2026

The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training

Rui Zhang, Hongwei Li, Yun Shen +6

The deployment of large language models (LLMs) raises significant ethical and safety concerns. While LLM alignment techniques are adopted to improve model safety and trustworthines…

cs.CR2026

When Safe Concepts Become Unsafe: Multi-Concept Compositional Vulnerabilities in Text-to-Image Models

Chaoshuo Zhang, Yibo Liang, Mengke Tian +7

Text-to-image (T2I) models are increasingly optimized for following user instructions faithfully. However, we find that this capability introduces a safety vulnerability we call Mu…

cs.CR2026

Benchmark of Benchmarks: Unpacking Influence and Code Repository Quality in LLM Safety Benchmarks

Junjie Chu, Xinyue Shen, Ye Leng +3

The rapid expansion of research in LLM safety presents challenges in tracking advancements, making benchmarks important evaluation infrastructures for identifying key trends and fa…