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Lucia Zheng

3 accepted papers

2025

LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain

NAACL 2025findings

Instruction tuning is an important step in making language models useful for direct user interaction. However, the legal domain is underrepresented in typical instruction datasets (e.g., only 10 out of 1600+ tasks in Super-NaturalInstructions). To study whether instruction tuning on legal datasets i…

2024

NLP Systems That Can’t Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helps

NAACL 2024long

The use of words to convey speaker’s intent is traditionally distinguished from the ‘mention’ of words for quoting what someone said, or pointing out properties of a word. Here we show that computationally modeling this use-mention distinction is crucial for dealing with counterspeech online. Counte…

2022

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

NeurIPS 2022accept

One concern with the rise of large language models lies with their potential for significant harm, particularly from pretraining on biased, obscene, copyrighted, and private information. Emerging ethical approaches have attempted to filter pretraining material, but such approaches have been ad hoc a…