1 citations · 1 across the 16 of their papers we have counts for
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The Straight and Narrow: Do LLMs Possess an Internal Moral Path?
Luoming Hu, Jingjie Zeng, Liang Yang +1
Enhancing the moral alignment of Large Language Models (LLMs) is a critical challenge in AI safety. Current alignment techniques often act as superficial guardrails, leaving the in…
Visual Puns from Idioms: An Iterative LLM-T2IM-MLLM Framework
Kelaiti Xiao, Liang Yang, Dongyu Zhang +2
We study idiom-based visual puns--images that align an idiom's literal and figurative meanings--and present an iterative framework that coordinates a large language model (LLM), a…
Fine-Grained Chinese Hate Speech Understanding: Span-Level Resources, Coded Term Lexicon, and Enhanced Detection Frameworks
Zewen Bai, Liang Yang, Shengdi Yin +2
The proliferation of hate speech has inflicted significant societal harm, with its intensity and directionality closely tied to specific targets and arguments. In recent years, num…
Commonality and Individuality! Integrating Humor Commonality with Speaker Individuality for Humor Recognition
Haohao Zhu, Junyu Lu, Zeyuan Zeng +4
Humor recognition aims to identify whether a specific speaker's text is humorous. Current methods for humor recognition mainly suffer from two limitations: (1) they solely focus on…
Is LLM an Overconfident Judge? Unveiling the Capabilities of LLMs in Detecting Offensive Language with Annotation Disagreement
Junyu Lu, Kai Ma, Kaichun Wang +5
Large Language Models (LLMs) have become essential for offensive language detection, yet their ability to handle annotation disagreement remains underexplored. Disagreement samples…
STATE ToxiCN: A Benchmark for Span-level Target-Aware Toxicity Extraction in Chinese Hate Speech Detection
Zewen Bai, Shengdi Yin, Junyu Lu +5
The proliferation of hate speech has caused significant harm to society. The intensity and directionality of hate are closely tied to the target and argument it is associated with.…