Alisa Liu

According to our database, Alisa Liu authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A Taxonomy of Ambiguity Types for NLP.

Margaret Y. Li, Alisa Liu, Zhaofeng Wu, Noah A. Smith

CoRR, 2024

Tuning Language Models by Proxy.

Alisa Liu, Xiaochuang Han, Yizhong Wang, Yulia Tsvetkov, Yejin Choi, Noah A. Smith

CoRR, 2024

2023

Inverse Scaling: When Bigger Isn't Better.

Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, Ethan Perez

CoRR, 2023

How Language Model Hallucinations Can Snowball.

Muru Zhang, Ofir Press, William Merrill, Alisa Liu, Noah A. Smith

CoRR, 2023

We're Afraid Language Models Aren't Modeling Ambiguity.

Alisa Liu, Zhaofeng Wu, Julian Michael, Alane Suhr, Peter West, Alexander Koller, Swabha Swayamdipta, Noah A. Smith, Yejin Choi

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?

Jaechan Lee, Alisa Liu, Orevaoghene Ahia, Hila Gonen, Noah A. Smith

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts.

Skyler Hallinan, Alisa Liu, Yejin Choi, Maarten Sap

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

Self-Instruct: Aligning Language Model with Self Generated Instructions.

Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi

CoRR, 2022

WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation.

Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Generated Knowledge Prompting for Commonsense Reasoning.

Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, Hannaneh Hajishirzi

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

On-the-Fly Controlled Text Generation with Experts and Anti-Experts.

Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, Yejin Choi

CoRR, 2021

DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts.

Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, Yejin Choi

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Incorporating Music Knowledge in Continual Dataset Augmentation for Music Generation.

Alisa Liu, Alexander Fang, Gaëtan Hadjeres, Prem Seetharaman, Bryan Pardo

CoRR, 2020

Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach.

Alexander Fang, Alisa Liu, Prem Seetharaman, Bryan Pardo

CoRR, 2020

Model Selection for Deep Audio Source Separation via Clustering Analysis.

Alisa Liu, Prem Seetharaman, Bryan Pardo

Proceedings of 5th the Workshop on Detection and Classification of Acoustic Scenes and Events 2020 (DCASE 2020), 2020

2019

Multi-sense Definition Modeling using Word Sense Decompositions.

Ruimin Zhu, Thanapon Noraset, Alisa Liu, Wenxin Jiang, Doug Downey

CoRR, 2019

CODAH: An Adversarially Authored Question-Answer Dataset for Common Sense.

Michael Chen, Mike D'Arcy, Alisa Liu, Jared Fernandez, Doug Downey

CoRR, 2019