Papers by Garrett Honke
Translation between Molecules and Natural Language (2022.emnlp-main)
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| Challenge: | MolT5 pretrains models on unlabeled natural language text and molecule strings . bringing a new drug to market can cost over a billion dollars and take over ten years . |
| Approach: | They propose a self-supervised learning framework for pretraining models on unlabeled natural language text and molecule strings. |
| Outcome: | The proposed framework pretrains models on unlabeled natural language text and molecule strings, and it generates high quality outputs. |
LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain (2025.findings-naacl)
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Joel Niklaus, Lucia Zheng, Arya D. McCarthy, Christopher Hahn, Brian M Rosen, Peter Henderson, Daniel E. Ho, Garrett Honke, Percy Liang, Christopher D Manning
| Challenge: | In general, instruction tuning is important for direct user interaction, but the legal domain is underrepresented in typical instruction datasets. |
| Approach: | They aggregate 58 annotated legal datasets and write instructions for each to create LawInstruct. |
| Outcome: | The proposed model improves on LegalBench across all model sizes, but no drop in MMLU. |