1 | Alisa Liu

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

Using expert and anti-expert LMs to rewrite toxic text for safety

Skyler Hallinan, Alisa Liu, Yejin Choi, Maarten Sap

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

We introduce a paradigm for dataset creation based on human and machine collaboration, and demonstrate its empirical effectiveness for collecting a new large-scale NLI dataset

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

Generated Knowledge Prompting for Commonsense Reasoning

Prompting GPT-3 to generate relevant background knowledge improves performance on a variety of commonsense reasoning tasks

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

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

Steering open-ended text generation toward desired or away from undesired attributes, using expert and anti-expert language models

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

Model Selection for Deep Audio Source Separation via Clustering Analysis

Ensemble model for audio source separation, using a confidence measure to mediate among domain-specific models

Alisa Liu, Prem Seetharaman, Bryan Pardo

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

An automatic, interpretable, and musically-motivated grading function for Bach chorales

Alex Fang, Alisa Liu, Prem Seetharaman, Bryan Pardo

Incorporating Music Knowledge in Continual Dataset Augmentation for Music Generation

A generative data augmentation method for music generation systems on a resource-constrained domain

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

CODAH: An Adversarially-Authored Question Answering Dataset for Common Sense

An adversarially-constructed dataset for common sense QA

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