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20152022
most citedLambdaNet: Probabilistic Type Inference using Graph Neural Networks

47 citations · 124 across the 20 of their papers we have counts for

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cs.CL20221 cited

Natural Language Deduction with Incomplete Information

Zayne Sprague, Kaj Bostrom, Swarat Chaudhuri +1

A growing body of work studies how to answer a question or verify a claim by generating a natural language "proof": a chain of deductive inferences yielding the answer based on a s…

cs.CL2022

Assessing Out-of-Domain Language Model Performance from Few Examples

Prasann Singhal, Jarad Forristal, Xi Ye +1

While pretrained language models have exhibited impressive generalization capabilities, they still behave unpredictably under certain domain shifts. In particular, a model may lear…

cs.CL20221 cited

Entity Cloze By Date: What LMs Know About Unseen Entities

Yasumasa Onoe, Michael J. Q. Zhang, Eunsol Choi +1

Language models (LMs) are typically trained once on a large-scale corpus and used for years without being updated. However, in a dynamic world, new entities constantly arise. We pr…

cs.CL2021

Cross-Lingual Fine-Grained Entity Typing

Nila Selvaraj, Yasumasa Onoe, Greg Durrett

The growth of cross-lingual pre-trained models has enabled NLP tools to rapidly generalize to new languages. While these models have been applied to tasks involving entities, their…

cs.CL202126 cited

CREAK: A Dataset for Commonsense Reasoning over Entity Knowledge

Yasumasa Onoe, Michael J. Q. Zhang, Eunsol Choi +1

Most benchmark datasets targeting commonsense reasoning focus on everyday scenarios: physical knowledge like knowing that you could fill a cup under a waterfall [Talmor et al., 201…

cs.CL2021

DISCO : efficient unsupervised decoding for discrete natural language problems via convex relaxation

Anish Acharya, Rudrajit Das

In this paper we study test time decoding; an ubiquitous step in almost all sequential text generation task spanning across a wide array of natural language processing (NLP) proble…