Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Just-DREAM-about-it: Figurative Language Understanding with DREAM-FLUTE
Figurative language (e.g., “he flew like the wind”) is challenging to understand, as it is hard to tell what implicit information is being conveyed from the surface form alone. We hypothesize that…
Webly Supervised Concept Expansion for General Purpose Vision Models
General purpose vision (GPV) systems [25] are models that are designed to solve a wide array of visual tasks without requiring architectural changes. Today, GPVs primarily learn both skills and…
SciFact-Open: Towards open-domain scientific claim verification
While research on scientific claim verification has led to the development of powerful systems that appear to approach human performance, these approaches have yet to be tested in a realistic…
Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation
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 control for compression…
Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs
Social intelligence and Theory of Mind (T O M), i.e., the ability to reason about the different mental states, intents, and reactions of all people involved, allow humans to effectively navigate and…
The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning
Humans have remarkable capacity to reason abductively and hypothesize about what lies beyond the literal content of an image. By identifying concrete visual clues scattered throughout a scene, we…
A Dataset of Alt Texts from HCI Publications
Figures in scientifc publications contain important information and results, and alt text is needed for blind and low vision readers to engage with their content. We conduct a study to characterize…
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation
While counterfactual data augmentation offers a promising step towards robust generalization in natural language processing, producing a set of counterfactuals that offer valuable inductive bias for…
Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering
Knowledge underpins reasoning. Recent research demonstrates that when relevant knowledge is provided as additional context to commonsense question answering (QA), it can substantially enhance the…
Towards Disturbance-Free Visual Mobile Manipulation
Deep reinforcement learning has shown promising results on an abundance of robotic tasks in simulation, including visual navigation and manipulation. Prior work generally aims to build embodied…