Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark
Commonsense AI has long been seen as a near impossible goal—until recently. Now, research interest has sharply increased with an influx of new benchmarks and models. We propose two new ways to…
MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations
We study conversational dialog in which there are many possible responses to a given history. We present the MultiTalk Dataset, a corpus of over 320,000 sentences of written conversational dialog…
Scruples: A Corpus of Community Ethical Judgments on 32, 000 Real-Life Anecdotes
As AI systems become an increasing part of people's everyday lives, it becomes ever more important that they understand people's ethical norms. Motivated by descriptive ethics, a field of study that…
GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation
Leaderboards have eased model development for many NLP datasets by standardizing their evaluation and delegating it to an independent external repository. Their adoption, however, is so far limited…
On-the-Fly Attention Modularization for Neural Generation
Despite considerable advancements with deep neural language models (LMs), neural text generation still suffers from degeneration: generated text is repetitive, generic, selfinconsistent, and lacking…
VinVL: Revisiting Visual Representations in Vision-Language Models
This paper presents a detailed study of improving visual representations for vision language (VL) tasks and develops an improved object detection model to provide object-centric representations of…
CLUE: A Chinese Language Understanding Evaluation Benchmark
We introduce CLUE, a Chinese Language Understanding Evaluation benchmark. It contains eight different tasks, including single-sentence classification, sentence pair classification, and machine…
Edited Media Understanding: Reasoning About Implications of Manipulated Images
Multimodal disinformation, from `deepfakes' to simple edits that deceive, is an important societal problem. Yet at the same time, the vast majority of media edits are harmless -- such as a filtered…
Text mining approaches for dealing with the rapidly expanding literature on COVID-19
More than 50 000 papers have been published about COVID-19 since the beginning of 2020 and several hundred new papers continue to be published every day. This incredible rate of scientific…
Belief Propagation Neural Networks
Learned neural solvers have successfully been used to solve combinatorial optimization and decision problems. More general counting variants of these problems, however, are still largely solved with…