24 citations · 28 across the 3 of their papers we have counts for
9 papers
Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features
Hannah Rashkin, David Reitter, Gaurav Singh Tomar +1
Knowledge-grounded dialogue systems are intended to convey information that is based on evidence provided in a given source text. We discuss the challenges of training a generative…
PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction
Xinyao Ma, Maarten Sap, Hannah Rashkin +1
Unconscious biases continue to be prevalent in modern text and media, calling for algorithms that can assist writers with bias correction. For example, a female character in a stor…
PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi +1
We propose the task of outline-conditioned story generation: given an outline as a set of phrases that describe key characters and events to appear in a story, the task is to gener…
Abductive Commonsense Reasoning
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya +6
Abductive reasoning is inference to the most plausible explanation. For example, if Jenny finds her house in a mess when she returns from work, and remembers that she left a window…
COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap +3
We present the first comprehensive study on automatic knowledge base construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet (Speer et…
Defending Against Neural Fake News
Rowan Zellers, Ari Holtzman, Hannah Rashkin +4
Recent progress in natural language generation has raised dual-use concerns. While applications like summarization and translation are positive, the underlying technology also migh…