Papers by Sean Xie

2 papers
Addressing Healthcare-related Racial and LGBTQ+ Biases in Pretrained Language Models (2024.findings-naacl)

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Challenge: Pretrained language models (PLMs) propagate social stigmas and stereotypes, a critical concern given their widespread use.
Approach: They adapt two intrinsic bias benchmarks to quantify racial and LGBTQ+ biases in prevalent PLMs and empirically evaluate the effectiveness of various debiasing methods in mitigating these biase.
Outcome: The proposed methods reduce biases without compromising performance in downstream tasks.
Proto-lm: A Prototypical Network-Based Framework for Built-in Interpretability in Large Language Models (2023.findings-emnlp)

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Challenge: Existing methods for interpreting LLMs are post hoc and focus on low-level features and lack of explainability at higher-level text units.
Approach: They propose a prototypical network-based white-box framework that allows LLMs to learn immediately interpretable embeddings during the fine-tuning stage while maintaining competitive performance.
Outcome: The proposed framework can learn interpretable embeddings during the fine-tuning stage while maintaining competitive performance.

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