activity
20162023
most citedRevisiting Pre-Trained Models for Chinese Natural Language Processing

565 citations · 1.4k across the 30 of their papers we have counts for

collaborators

30 papers

cs.CL2023

Multi-Stage Coarse-to-Fine Contrastive Learning for Conversation Intent Induction

Caiyuan Chu, Ya Li, Yifan Liu +4

Intent recognition is critical for task-oriented dialogue systems. However, for emerging domains and new services, it is difficult to accurately identify the key intent of a conver…

cs.CL2021★ 3 cited

SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary

Jiaan Wang, Zhixu Li, Qiang Yang +4

Sports game summarization aims to generate news articles from live text commentaries. A recent state-of-the-art work, SportsSum, not only constructs a large benchmark dataset, but…

cs.CL2021★ 7 cited

Adversarial Training for Machine Reading Comprehension with Virtual Embeddings

Ziqing Yang, Yiming Cui, Chenglei Si +4

Adversarial training (AT) as a regularization method has proved its effectiveness on various tasks. Though there are successful applications of AT on some NLP tasks, the distinguis…

cs.CL2021★ 3 cited

Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering

Nan Shao, Yiming Cui, Ting Liu +2

Retrieving information from correlative paragraphs or documents to answer open-domain multi-hop questions is very challenging. To deal with this challenge, most of the existing wor…

cs.CL2020★ 2 cited

Unsupervised Explanation Generation for Machine Reading Comprehension

Yiming Cui, Ting Liu, Shijin Wang +1

With the blooming of various Pre-trained Language Models (PLMs), Machine Reading Comprehension (MRC) has embraced significant improvements on various benchmarks and even surpass hu…

cs.CL2020★ 89 cited

CharBERT: Character-aware Pre-trained Language Model

Wentao Ma, Yiming Cui, Chenglei Si +3

Most pre-trained language models (PLMs) construct word representations at subword level with Byte-Pair Encoding (BPE) or its variations, by which OOV (out-of-vocab) words are almos…