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20192022
most citedScaling Instruction-Finetuned Language Models

1.2k citations · 1.2k across the 7 of their papers we have counts for

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cs.CL20226 cited

Active Learning Over Multiple Domains in Natural Language Tasks

Shayne Longpre, Julia Reisler, Edward Greg Huang +4

Studies of active learning traditionally assume the target and source data stem from a single domain. However, in realistic applications, practitioners often require active learnin…

cs.CL20211 cited

Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP

Anthony Chen, Pallavi Gudipati, Shayne Longpre +2

Retrieval is a core component for open-domain NLP tasks. In open-domain tasks, multiple entities can share a name, making disambiguation an inherent yet under-explored problem. We…

cs.CL2020

Pivot Through English: Reliably Answering Multilingual Questions without Document Retrieval

Ivan Montero, Shayne Longpre, Ni Lao +2

Existing methods for open-retrieval question answering in lower resource languages (LRLs) lag significantly behind English. They not only suffer from the shortcomings of non-Englis…

cs.CL2020

On the Transferability of Minimal Prediction Preserving Inputs in Question Answering

Shayne Longpre, Yi Lu, Christopher DuBois

Recent work (Feng et al., 2018) establishes the presence of short, uninterpretable input fragments that yield high confidence and accuracy in neural models. We refer to these as Mi…

cs.CL2019

An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering

Shayne Longpre, Yi Lu, Zhucheng Tu +1

To produce a domain-agnostic question answering model for the Machine Reading Question Answering (MRQA) 2019 Shared Task, we investigate the relative benefits of large pre-trained…