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Luyang Lin

2 accepted papers

2025

Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception

COLING 2025main

The pervasive spread of misinformation and disinformation in social media underscores the critical importance of detecting media bias. While robust Large Language Models (LLMs) have emerged as foundational tools for bias prediction, concerns about inherent biases within these models persist. In this…

Cited by 36SourcePDFScholar
2024

LLMEdgeRefine: Enhancing Text Clustering with LLM-Based Boundary Point Refinement

EMNLP 2024main

Text clustering is a fundamental task in natural language processing with numerous applications. However, traditional clustering methods often struggle with domain-specific fine-tuning and the presence of outliers. To address these challenges, we introduce LLMEdgeRefine, an iterative clustering meth…