Papers by Terrance Liu
Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies (2025.emnlp-main)
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| Challenge: | Large language models (LLMs) exhibit unexpected failures in which they are confidently incorrect. |
| Approach: | They propose a method for calibrating SQL outputs that leverages structured nature to provide more granular signals of correctness. |
| Outcome: | The proposed method improves on two popular text-to-SQL datasets and provides a confidence score that is calibrated. |
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data (2021.acl-long)
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Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nick Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov, Louis-Philippe Morency
| Challenge: | Mental health conditions remain underdiagnosed in many countries despite access to advanced medical care . a new approach to learn mood markers from mobile data is needed to improve accuracy and improve learning from typed text. |
| Approach: | They propose to use mobile data to learn mood markers without identifying users through personal or protected attributes. |
| Outcome: | The proposed model obfuscates user identities while remaining predictive . future directions include better models and pre-learning from typed text . |