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20192023
most citedMulti-Task Deep Neural Networks for Natural Language Understanding

221 citations · 1.2k across the 40 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CL2021★ 8 cited

Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention

Yichong Xu, Chenguang Zhu, Shuohang Wang +7

Most of today's AI systems focus on using self-attention mechanisms and transformer architectures on large amounts of diverse data to achieve impressive performance gains. In this…

cs.CL2021

DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Pengcheng He, Jianfeng Gao, Weizhu Chen

This paper presents a new pre-trained language model, DeBERTaV3, which improves the original DeBERTa model by replacing mask language modeling (MLM) with replaced token detection (…

cs.CL2021

ARCH: Efficient Adversarial Regularized Training with Caching

Simiao Zuo, Chen Liang, Haoming Jiang +5

Adversarial regularization can improve model generalization in many natural language processing tasks. However, conventional approaches are computationally expensive since they nee…

cs.LG2021★ 1 cited

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization

Chen Liang, Simiao Zuo, Minshuo Chen +5

The Lottery Ticket Hypothesis suggests that an over-parametrized network consists of ``lottery tickets'', and training a certain collection of them (i.e., a subnetwork) can match t…

cs.LG2021

Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach

Simiao Zuo, Chen Liang, Haoming Jiang +5

Adversarial regularization has been shown to improve the generalization performance of deep learning models in various natural language processing tasks. Existing works usually for…

cs.CL2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Sewon Min, Jordan Boyd-Graber, Chris Alberti +50

We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and…