30 citations · 31 across the 3 of their papers we have counts for
7 papers · 1 filter
Generating Sequences by Learning to Self-Correct
Sean Welleck, Ximing Lu, Peter West +4
Sequence generation applications require satisfying semantic constraints, such as ensuring that programs are correct, using certain keywords, or avoiding undesirable content. Langu…
Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation
Melanie Sclar, Peter West, Sachin Kumar +2
We present Referee, a novel framework for sentence summarization that can be trained reference-free (i.e., requiring no gold summaries for supervision), while allowing direct contr…
Probing Factually Grounded Content Transfer with Factual Ablation
Peter West, Chris Quirk, Michel Galley +1
Despite recent success, large neural models often generate factually incorrect text. Compounding this is the lack of a standard automatic evaluation for factuality--it cannot be me…
NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints
Ximing Lu, Peter West, Rowan Zellers +3
Conditional text generation often requires lexical constraints, i.e., which words should or shouldn't be included in the output text. While the dominant recipe for conditional text…
Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning
Lianhui Qin, Vered Shwartz, Peter West +5
Abductive and counterfactual reasoning, core abilities of everyday human cognition, require reasoning about what might have happened at time t, while conditioning on multiple conte…
Unsupervised Commonsense Question Answering with Self-Talk
Vered Shwartz, Peter West, Ronan Le Bras +2
Natural language understanding involves reading between the lines with implicit background knowledge. Current systems either rely on pre-trained language models as the sole implici…