activity
20152022
most citedWhat do you learn from context? Probing for sentence structure in contextualized word representations

139 citations · 237 across the 27 of their papers we have counts for

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Showing 2019Show all

16 papers · 1 filter

cs.CL2019

Reading the Manual: Event Extraction as Definition Comprehension

Yunmo Chen, Tongfei Chen, Seth Ebner +2

We ask whether text understanding has progressed to where we may extract event information through incremental refinement of bleached statements derived from annotation manuals. Su…

cs.DS20191 cited

Exact and/or Fast Nearest Neighbors

Matthew Francis-Landau, Benjamin Van Durme

Prior methods for retrieval of nearest neighbors in high dimensions are fast and approximate--providing probabilistic guarantees of returning the correct answer--or slow and exact…

cs.CL2019

Multi-Sentence Argument Linking

Seth Ebner, Patrick Xia, Ryan Culkin +2

We present a novel document-level model for finding argument spans that fill an event's roles, connecting related ideas in sentence-level semantic role labeling and coreference res…

cs.CL2019

Universal Decompositional Semantic Parsing

Elias Stengel-Eskin, Aaron Steven White, Sheng Zhang +1

We introduce a transductive model for parsing into Universal Decompositional Semantics (UDS) representations, which jointly learns to map natural language utterances into UDS graph…

cs.CL2019

The Universal Decompositional Semantics Dataset and Decomp Toolkit

Aaron Steven White, Elias Stengel-Eskin, Siddharth Vashishtha +9

We present the Universal Decompositional Semantics (UDS) dataset (v1.0), which is bundled with the Decomp toolkit (v0.1). UDS1.0 unifies five high-quality, decompositional semantic…

cs.CL2019

Uncertain Natural Language Inference

Tongfei Chen, Zhengping Jiang, Adam Poliak +2

We introduce Uncertain Natural Language Inference (UNLI), a refinement of Natural Language Inference (NLI) that shifts away from categorical labels, targeting instead the direct pr…