Alisa Liu

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 27

Top Topics

Source Separation

Clustering Analysis

Text Generation

Top Venues

EMNLP (Findings)

Publications

Alisa Liu, Xiaochuang Han, Yizhong Wang, Yulia Tsvetkov, Yejin Choi, Noah A. Smith
Tuning Language Models by Proxy. CoRR (2024)
Margaret Y. Li, Alisa Liu, Zhaofeng Wu, Noah A. Smith
A Taxonomy of Ambiguity Types for NLP. CoRR (2024)
Ruizhe Shi, Yifang Chen, Yushi Hu, Alisa Liu, Hannaneh Hajishirzi, Noah A. Smith, Simon S. Du
Decoding-Time Language Model Alignment with Multiple Objectives. CoRR (2024)
Jonathan Hayase, Alisa Liu, Yejin Choi, Sewoong Oh, Noah A. Smith
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data? CoRR (2024)
Alisa Liu, Zhaofeng Wu, Julian Michael, Alane Suhr, Peter West, Alexander Koller, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
We're Afraid Language Models Aren't Modeling Ambiguity. EMNLP (2023)
Jaechan Lee, Alisa Liu, Orevaoghene Ahia, Hila Gonen, Noah A. Smith
That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context? CoRR (2023)
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi
Self-Instruct: Aligning Language Models with Self-Generated Instructions. ACL (1) (2023)
Muru Zhang, Ofir Press, William Merrill, Alisa Liu, Noah A. Smith
How Language Model Hallucinations Can Snowball. CoRR (2023)
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
Inverse Scaling: When Bigger Isn't Better. CoRR (2023)
Alisa Liu, Zhaofeng Wu, Julian Michael, Alane Suhr, Peter West, Alexander Koller, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
We're Afraid Language Models Aren't Modeling Ambiguity. CoRR (2023)
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
Inverse Scaling: When Bigger Isn't Better. Trans. Mach. Learn. Res. 2023 (2023)
Jaechan Lee, Alisa Liu, Orevaoghene Ahia, Hila Gonen, Noah A. Smith
That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context? EMNLP (Findings) (2023)
Skyler Hallinan, Alisa Liu, Yejin Choi, Maarten Sap
Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts. ACL (2) (2023)
Skyler Hallinan, Alisa Liu, Yejin Choi, Maarten Sap
Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts. CoRR (2022)
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi
Self-Instruct: Aligning Language Model with Self Generated Instructions. CoRR (2022)
Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, Hannaneh Hajishirzi
Generated Knowledge Prompting for Commonsense Reasoning. ACL (1) (2022)
Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation. EMNLP (Findings) (2022)
Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation. CoRR (2022)
Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, Hannaneh Hajishirzi
Generated Knowledge Prompting for Commonsense Reasoning. CoRR (2021)
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, Yejin Choi
On-the-Fly Controlled Text Generation with Experts and Anti-Experts. CoRR (2021)
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, Yejin Choi
DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts. ACL/IJCNLP (1) (2021)
Alexander Fang, Alisa Liu, Prem Seetharaman, Bryan Pardo
Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach. CoRR (2020)
Alisa Liu, Prem Seetharaman, Bryan Pardo
Model Selection for Deep Audio Source Separation via Clustering Analysis. DCASE (2020)
Alisa Liu, Alexander Fang, Gaëtan Hadjeres, Prem Seetharaman, Bryan Pardo
Incorporating Music Knowledge in Continual Dataset Augmentation for Music Generation. CoRR (2020)
Michael Chen, Mike D'Arcy, Alisa Liu, Jared Fernandez, Doug Downey
CODAH: An Adversarially Authored Question-Answer Dataset for Common Sense. CoRR (2019)
Alisa Liu, Prem Seetharaman, Bryan Pardo
Model selection for deep audio source separation via clustering analysis. CoRR (2019)
Ruimin Zhu, Thanapon Noraset, Alisa Liu, Wenxin Jiang, Doug Downey
Multi-sense Definition Modeling using Word Sense Decompositions. CoRR (2019)