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20152025
most citedLambdaNet: Probabilistic Type Inference using Graph Neural Networks

47 citations · 125 across the 23 of their papers we have counts for

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Showing 2021Show all

12 papers · 1 filter

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…

cs.CL20211 cited

Dissecting Generation Modes for Abstractive Summarization Models via Ablation and Attribution

Jiacheng Xu, Greg Durrett

Despite the prominence of neural abstractive summarization models, we know little about how they actually form summaries and how to understand where their decisions come from. We p…

cs.PL20211 cited

Web Question Answering with Neurosymbolic Program Synthesis

Qiaochu Chen, Aaron Lamoreaux, Xinyu Wang +3

In this paper, we propose a new technique based on program synthesis for extracting information from webpages. Given a natural language query and a few labeled webpages, our method…

cs.CL2021

Did they answer? Subjective acts and intents in conversational discourse

Elisa Ferracane, Greg Durrett, Junyi Jessy Li +1

Discourse signals are often implicit, leaving it up to the interpreter to draw the required inferences. At the same time, discourse is embedded in a social context, meaning that in…