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Jeremy Qin

2 accepted papers

2025

SHADES: Towards a Multilingual Assessment of Stereotypes in Large Language Models

NAACL 2025long

Large Language Models (LLMs) reproduce and exacerbate the social biases present in their training data, and resources to quantify this issue are limited. While research has attempted to identify and mitigate such biases, most efforts have been concentrated around English, lagging the rapid advanceme…

Cited by 1SourcePDFScholar
2024

Enhancing Healthcare LLM Trust with Atypical Presentations Recalibration

EMNLP 2024finding

Black-box large language models (LLMs) are increasingly deployed in various environments, making it essential for these models to effectively convey their confidence and uncertainty, especially in high-stakes settings. However, these models often exhibit overconfidence, leading to potential risks an…