Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
TIMEDIAL: Temporal Commonsense Reasoning in Dialog
Everyday conversations require understanding everyday events, which in turn, requires understanding temporal commonsense concepts interwoven with those events. Despite recent progress with massive…
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models
A common approach to solve complex tasks is by breaking them down into simple sub-problems that can then be solved by simpler modules. However, these approaches often need to be designed and trained…
Extracting a Knowledge Base of Mechanisms from COVID-19 Papers
The urgency of mitigating COVID-19 has spawned a large and diverse body of scientific literature that is challenging for researchers to navigate. This explosion of information has stimulated…
SmBoP: Semi-autoregressive Bottom-up Semantic Parsing
The de-facto standard decoding method for semantic parsing in recent years has been to autoregressively decode the abstract syntax tree of the target program using a top-down depth-first traversal.…
Temporal Reasoning on Implicit Events from Distant Supervision
Existing works on temporal reasoning among events described in text focus on modeling relationships between explicitly mentioned events and do not handle event end time effectively. However, human…
"I'm Not Mad": Commonsense Implications of Negation and Contradiction
Natural language inference requires reasoning about contradictions, negations, and their commonsense implications. Given a simple premise (e.g., “I’m mad at you”), humans can reason about the…
A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers
Readers of academic research papers often read with the goal of answering specific questions. Question Answering systems that can answer those questions can make consumption of the content much more…
Choose Your Own Adventure: Paired Suggestions in Collaborative Writing for Evaluating Story Generation Models
Story generation is an open-ended and subjective task, which poses a challenge for evaluating story generation models. We present Choose Your Own Adventure, a collaborative writing setup for…
XOR QA: Cross-lingual Open-Retrieval Question Answering
Multilingual question answering tasks typically assume that answers exist in the same language as the question. Yet in practice, many languages face both information scarcity—where languages have…
Probing Contextual Language Models for Common Ground with Visual Representations
The success of large-scale contextual language models has attracted great interest in probing what is encoded in their representations. In this work, we consider a new question: to what extent…