5 papers · 1 filter
Beyond Over-Refusal: Scenario-Based Diagnostics and Post-Hoc Mitigation for Exaggerated Refusals in LLMs
Shuzhou Yuan, Ercong Nie, Yinuo Sun +3
Large language models (LLMs) frequently produce false refusals, declining benign requests that contain terms resembling unsafe queries. We address this challenge by introducing two…
CoDAE: Adapting Large Language Models for Education via Chain-of-Thought Data Augmentation
Shuzhou Yuan, William LaCroix, Hardik Ghoshal +2
Large Language Models (LLMs) are increasingly employed as AI tutors due to their scalability and potential for personalized instruction. However, off-the-shelf LLMs often underperf…
Hateful Person or Hateful Model? Investigating the Role of Personas in Hate Speech Detection by Large Language Models
Shuzhou Yuan, Ercong Nie, Mario Tawfelis +3
Hate speech detection is a socially sensitive and inherently subjective task, with judgments often varying based on personal traits. While prior work has examined how socio-demogra…
LLM in the Loop: Creating the ParaDeHate Dataset for Hate Speech Detoxification
Shuzhou Yuan, Ercong Nie, Lukas Kouba +4
Detoxification, the task of rewriting harmful language into non-toxic text, has become increasingly important amid the growing prevalence of toxic content online. However, high-qua…
Can Hallucinations Help? Boosting LLMs for Drug Discovery
Shuzhou Yuan, Zhan Qu, Ashish Yashwanth Kangen +1
Hallucinations in large language models (LLMs), plausible but factually inaccurate text, are often viewed as undesirable. However, recent work suggests that such outputs may hold c…