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个人简介
My research focus is on interpretability of large language models, exploring how they encode linguistic and factual information about the world. My primary focus lies in leveraging interpretability as a strategic tool for enhancing model performance, specifically addressing robustness and safety concerns, with the ultimate goal of improving transparency and trustworthiness. Thus, my work revolves around developing new methods for evaluating, understanding and improving the robustness of NLP models, ultimately aiming to create models that are both powerful and responsible.
研究兴趣
论文共 9 篇作者统计合作学者相似作者
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Annual Meeting of the Association for Computational Linguisticspp.9713-9728, (2024)
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CoRR (2023)
2023 IEEE/CVF International Conference on Computer Vision (ICCV) (2023): 7030-7038
arXiv (Cornell University) (2022)
CoRR (2022)
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作者统计
#Papers: 9
#Citation: 231
H-Index: 4
G-Index: 4
Sociability: 3
Diversity: 1
Activity: 8
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