activity
20192023
most citedOn the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation

8 citations · 20 across the 11 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.LG2022

Responsible Active Learning via Human-in-the-loop Peer Study

Yu-Tong Cao, Jingya Wang, Baosheng Yu +1

Active learning has been proposed to reduce data annotation efforts by only manually labelling representative data samples for training. Meanwhile, recent active learning applicati…

cs.LG2022

Knowledge-Aware Federated Active Learning with Non-IID Data

Yu-Tong Cao, Ye Shi, Baosheng Yu +2

Federated learning enables multiple decentralized clients to learn collaboratively without sharing the local training data. However, the expensive annotation cost to acquire data l…

cs.CL2022

TASA: Deceiving Question Answering Models by Twin Answer Sentences Attack

Yu Cao, Dianqi Li, Meng Fang +4

We present Twin Answer Sentences Attack (TASA), an adversarial attack method for question answering (QA) models that produces fluent and grammatical adversarial contexts while main…

cs.CL2022★ 8 cited

On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation

Changtong Zan, Liang Ding, Li Shen +3

Pre-Training (PT) of text representations has been successfully applied to low-resource Neural Machine Translation (NMT). However, it usually fails to achieve notable gains (someti…

cs.CL2022

Interpretable Proof Generation via Iterative Backward Reasoning

Hanhao Qu, Yu Cao, Jun Gao +2

We present IBR, an Iterative Backward Reasoning model to solve the proof generation tasks on rule-based Question Answering (QA), where models are required to reason over a series o…

cs.CL2022★ 1 cited

A Model-Agnostic Data Manipulation Method for Persona-based Dialogue Generation

Yu Cao, Wei Bi, Meng Fang +2

Towards building intelligent dialogue agents, there has been a growing interest in introducing explicit personas in generation models. However, with limited persona-based dialogue…