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20172022
most citedWhat do you learn from context? Probing for sentence structure in contextualized word representations

139 citations · 145 across the 6 of their papers we have counts for

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13 papers · 1 filter

cs.CL20221 cited

Automatic Document Selection for Efficient Encoder Pretraining

Yukun Feng, Patrick Xia, Benjamin Van Durme +1

Building pretrained language models is considered expensive and data-intensive, but must we increase dataset size to achieve better performance? We propose an alternative to larger…

cs.CL2021

On Generalization in Coreference Resolution

Shubham Toshniwal, Patrick Xia, Sam Wiseman +2

While coreference resolution is defined independently of dataset domain, most models for performing coreference resolution do not transfer well to unseen domains. We consolidate a…

cs.CL2021

Moving on from OntoNotes: Coreference Resolution Model Transfer

Patrick Xia, Benjamin Van Durme

Academic neural models for coreference resolution (coref) are typically trained on a single dataset, OntoNotes, and model improvements are benchmarked on that same dataset. However…

cs.CL2021

LOME: Large Ontology Multilingual Extraction

Patrick Xia, Guanghui Qin, Siddharth Vashishtha +7

We present LOME, a system for performing multilingual information extraction. Given a text document as input, our core system identifies spans of textual entity and event mentions…

cs.CL2020

CopyNext: Explicit Span Copying and Alignment in Sequence to Sequence Models

Abhinav Singh, Patrick Xia, Guanghui Qin +2

Copy mechanisms are employed in sequence to sequence models (seq2seq) to generate reproductions of words from the input to the output. These frameworks, operating at the lexical ty…

cs.CL20205 cited

Which *BERT? A Survey Organizing Contextualized Encoders

Patrick Xia, Shijie Wu, Benjamin Van Durme

Pretrained contextualized text encoders are now a staple of the NLP community. We present a survey on language representation learning with the aim of consolidating a series of sha…