activity
20162026
most citedLongformer: The Long-Document Transformer

2.2k citations · 3.1k across the 54 of their papers we have counts for

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Showing 2022 · cs.CLShow all

6 papers · 2 filters

cs.CL2022★ 4 cited

Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval

John Giorgi, Luca Soldaini, Bo Wang +4

Multi-document summarization (MDS) assumes a set of topic-related documents are provided as input. In practice, this document set is not always available; it would need to be retri…

cs.CL2022★ 7 cited

SciRepEval: A Multi-Format Benchmark for Scientific Document Representations

Amanpreet Singh, Mike D'Arcy, Arman Cohan +2

Learned representations of scientific documents can serve as valuable input features for downstream tasks without further fine-tuning. However, existing benchmarks for evaluating t…

cs.CL2022★ 4 cited

SciFact-Open: Towards open-domain scientific claim verification

David Wadden, Kyle Lo, Bailey Kuehl +4

While research on scientific claim verification has led to the development of powerful systems that appear to approach human performance, these approaches have yet to be tested in…

cs.CL2022★ 1 cited

Embedding Recycling for Language Models

Jon Saad-Falcon, Amanpreet Singh, Luca Soldaini +3

Real-world applications of neural language models often involve running many different models over the same corpus. The high computational cost of these runs has led to interest in…

cs.CL2022★ 3 cited

Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires

Thong Nguyen, Andrew Yates, Ayah Zirikly +2

Automated methods have been widely used to identify and analyze mental health conditions (e.g., depression) from various sources of information, including social media. Yet, deploy…

cs.CL2022★ 1 cited

Generating Scientific Claims for Zero-Shot Scientific Fact Checking

Dustin Wright, David Wadden, Kyle Lo +4

Automated scientific fact checking is difficult due to the complexity of scientific language and a lack of significant amounts of training data, as annotation requires domain exper…