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Featured Co-authors

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∙ 06/11/2023

Multi-Source Test-Time Adaptation as Dueling Bandits for Extractive Question Answering

In this work, we study multi-source test-time model adaptation from user...

0 Hai Ye, et al. ∙

∙ 04/25/2023

Test-Time Adaptation with Perturbation Consistency Learning

Currently, pre-trained language models (PLMs) do not cope well with the ...

0 Yi Su, et al. ∙

∙ 02/09/2023

Robust Question Answering against Distribution Shifts with Test-Time Adaptation: An Empirical Study

A deployed question answering (QA) model can easily fail when the test d...

0 Hai Ye, et al. ∙

∙ 06/06/2021

On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation

Adapter-based tuning has recently arisen as an alternative to fine-tunin...

0 Ruidan He, et al. ∙

∙ 09/24/2020

Feature Adaptation of Pre-Trained Language Models across Languages and Domains for Text Classification

Adapting pre-trained language models (PrLMs) (e.g., BERT) to new domains...

0 Hai Ye, et al. ∙

∙ 07/25/2019

Deep Ranking Based Cost-sensitive Multi-label Learning for Distant Supervision Relation Extraction

Knowledge base provides a potential way to improve the intelligence of i...

0 Hai Ye, et al. ∙

∙ 06/03/2019

Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization

Semantic parsing aims to transform natural language (NL) utterances into...

0 Hai Ye, et al. ∙

∙ 08/21/2018

Semi-Supervised Learning for Neural Keyphrase Generation

We study the problem of generating keyphrases that summarize the key poi...

0 Hai Ye, et al. ∙

∙ 02/23/2018

Interpretable Charge Predictions for Criminal Cases: Learning to Generate Court Views from Fact Descriptions

In this paper, we propose to study the problem of COURT VIEW GENeration ...

0 Hai Ye, et al. ∙

∙ 12/22/2016

Jointly Extracting Relations with Class Ties via Effective Deep Ranking

Connections between relations in relation extraction, which we call clas...

0 Hai Ye, et al. ∙

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