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20172026
most citedHellaSwag: Can a Machine Really Finish Your Sentence?

42 citations · 158 across the 42 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

cs.CV2019

ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

Mohit Shridhar, Jesse Thomason, Daniel Gordon +5

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

cs.CL2019

PIQA: Reasoning about Physical Commonsense in Natural Language

Yonatan Bisk, Rowan Zellers, Ronan Le Bras +2

To apply eyeshadow without a brush, should I use a cotton swab or a toothpick? Questions requiring this kind of physical commonsense pose a challenge to today's natural language un…

cs.CL2019

Robust Navigation with Language Pretraining and Stochastic Sampling

Xiujun Li, Chunyuan Li, Qiaolin Xia +5

Core to the vision-and-language navigation (VLN) challenge is building robust instruction representations and action decoding schemes, which can generalize well to previously unsee…

cs.CL201942 cited

HellaSwag: Can a Machine Really Finish Your Sentence?

Rowan Zellers, Ari Holtzman, Yonatan Bisk +2

Recent work by Zellers et al. (2018) introduced a new task of commonsense natural language inference: given an event description such as "A woman sits at a piano," a machine must s…

cs.CL2019

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…

cs.CL201911 cited

Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation

Liyiming Ke, Xiujun Li, Yonatan Bisk +6

We present the Frontier Aware Search with backTracking (FAST) Navigator, a general framework for action decoding, that achieves state-of-the-art results on the Room-to-Room (R2R) V…