activity
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 2020Show all

16 papers · 1 filter

cs.CL2020

Conditional Generation of Temporally-ordered Event Sequences

Shih-Ting Lin, Nathanael Chambers, Greg Durrett

Models of narrative schema knowledge have proven useful for a range of event-related tasks, but they typically do not capture the temporal relationships between events. We propose…

cs.CL2020

Evaluating Factuality in Generation with Dependency-level Entailment

Tanya Goyal, Greg Durrett

Despite significant progress in text generation models, a serious limitation is their tendency to produce text that is factually inconsistent with information in the input. Recent…

cs.CL2020

Compressive Summarization with Plausibility and Salience Modeling

Shrey Desai, Jiacheng Xu, Greg Durrett

Compressive summarization systems typically rely on a crafted set of syntactic rules to determine what spans of possible summary sentences can be deleted, then learn a model of wha…

cs.CL2020

Understanding Neural Abstractive Summarization Models via Uncertainty

Jiacheng Xu, Shrey Desai, Greg Durrett

An advantage of seq2seq abstractive summarization models is that they generate text in a free-form manner, but this flexibility makes it difficult to interpret model behavior. In t…

cs.CL2020

Inquisitive Question Generation for High Level Text Comprehension

Wei-Jen Ko, Te-Yuan Chen, Yiyan Huang +2

Inquisitive probing questions come naturally to humans in a variety of settings, but is a challenging task for automatic systems. One natural type of question to ask tries to fill…

cs.CL2020

Effective Distant Supervision for Temporal Relation Extraction

Xinyu Zhao, Shih-ting Lin, Greg Durrett

A principal barrier to training temporal relation extraction models in new domains is the lack of varied, high quality examples and the challenge of collecting more. We present a m…