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20152022
most citedAUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

195 citations · 691 across the 35 of their papers we have counts for

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24 papers · 1 filter

cs.CL20226 cited

DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings

Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo +7

We propose DiffCSE, an unsupervised contrastive learning framework for learning sentence embeddings. DiffCSE learns sentence embeddings that are sensitive to the difference between…

cs.CL202112 cited

PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition

Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu +7

Self-supervised speech representation learning (speech SSL) has demonstrated the benefit of scale in learning rich representations for Automatic Speech Recognition (ASR) with limit…

cs.CL20212 cited

Complementary Evidence Identification in Open-Domain Question Answering

Xiangyang Mou, Mo Yu, Shiyu Chang +3

This paper proposes a new problem of complementary evidence identification for open-domain question answering (QA). The problem aims to efficiently find a small set of passages tha…

cs.CL20201 cited

Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning

Xiaoxiao Guo, Mo Yu, Yupeng Gao +3

Interactive Fiction (IF) games with real human-written natural language texts provide a new natural evaluation for language understanding techniques. In contrast to previous text g…

cs.CL20202 cited

Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games

Yufei Feng, Mo Yu, Wenhan Xiong +6

We propose the new problem of learning to recover reasoning chains from weakly supervised signals, i.e., the question-answer pairs. We propose a cooperative game approach to deal w…

cs.CL20191 cited

Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering

Wenhan Xiong, Mo Yu, Xiaoxiao Guo +4

A key challenge of multi-hop question answering (QA) in the open-domain setting is to accurately retrieve the supporting passages from a large corpus. Existing work on open-domain…