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Research - Papers

Explore a selection of our published work on a variety of key research challenges in AI.

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The Right Tool for the Job: Matching Model and Instance Complexities

Roy SchwartzGabi StanovskySwabha SwayamdiptaNoah A. Smith
2020
ACL

As NLP models become larger, executing a trained model requires significant computational resources incurring monetary and environmental costs. To better respect a given inference budget, we propose… 

Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness?

Alon JacoviYoav Goldberg
2020
ACL

With the growing popularity of deep-learning based NLP models, comes a need for interpretable systems. But what is interpretability, and what constitutes a high-quality interpretation? In this… 

Unsupervised Domain Clusters in Pretrained Language Models

Roee AharoniYoav Goldberg
2020
ACL

The notion of "in-domain data" in NLP is often over-simplistic and vague, as textual data varies in many nuanced linguistic aspects such as topic, style or level of formality. In addition, domain… 

Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering

Ben BoginSanjay SubramanianMatt GardnerJonathan Berant
2020
TACL

Answering questions that involve multi-step reasoning requires decomposing them and using the answers of intermediate steps to reach the final answer. However, state-ofthe-art models in grounded… 

Procedural Reading Comprehension with Attribute-Aware Context Flow

Aida AminiAntoine BosselutBhavana Dalvi MishraHannaneh Hajishirzi
2020
AKBC

Procedural texts often describe processes (e.g., photosynthesis and cooking) that happen over entities (e.g., light, food). In this paper, we introduce an algorithm for procedural reading… 

ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

Mohit ShridharJesse ThomasonDaniel GordonDieter Fox
2020
CVPR

We present ALFRED (Action Learning From Realistic Environments and Directives), a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions… 

Butterfly Transform: An Efficient FFT Based Neural Architecture Design

Keivan AlizadehAli FarhadiMohammad Rastegari
2020
CVPR

In this paper, we introduce the Butterfly Transform (BFT), a light weight channel fusion method that reduces the computational complexity of point-wise convolutions from O(n^2) of conventional… 

RoboTHOR: An Open Simulation-to-Real Embodied AI Platform

Matt DeitkeWinson HanAlvaro HerrastiAli Farhadi
2020
CVPR

Visual recognition ecosystems (e.g. ImageNet, Pascal, COCO) have undeniably played a prevailing role in the evolution of modern computer vision. We argue that interactive and embodied visual AI has… 

Use the Force, Luke! Learning to Predict Physical Forces by Simulating Effects

Kiana EhsaniShubham TulsianiSaurabh GuptaAbhinav Gupta
2020
CVPR

When we humans look at a video of human-object interaction, we can not only infer what is happening but we can even extract actionable information and imitate those interactions. On the other hand,… 

Visual Reaction: Learning to Play Catch with Your Drone

Kuo-Hao ZengRoozbeh MottaghiLuca WeihsAli Farhadi
2020
CVPR

In this paper we address the problem of visual reaction: the task of interacting with dynamic environments where the changes in the environment are not necessarily caused by the agents itself.…