activity
20172023
most citedALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

75 citations · 374 across the 37 of their papers we have counts for

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18 papers · 1 filter

cs.CL20222 cited

Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios

Ngoc Dang Nguyen, Lan Du, Wray Buntine +2

Domain adaptation is an effective solution to data scarcity in low-resource scenarios. However, when applied to token-level tasks such as bioNER, domain adaptation methods often su…

cs.CL20213 cited

AES Systems Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses

Yaman Kumar Singla, Swapnil Parekh, Somesh Singh +3

Deep-learning based Automatic Essay Scoring (AES) systems are being actively used by states and language testing agencies alike to evaluate millions of candidates for life-changing…

cs.CL2021

Perception Point: Identifying Critical Learning Periods in Speech for Bilingual Networks

Anuj Saraswat, Mehar Bhatia, Yaman Kumar Singla +2

Recent studies in speech perception have been closely linked to fields of cognitive psychology, phonology, and phonetics in linguistics. During perceptual attunement, a critical an…

cs.CL2021

MINIMAL: Mining Models for Data Free Universal Adversarial Triggers

Swapnil Parekh, Yaman Singla Kumar, Somesh Singh +3

It is well known that natural language models are vulnerable to adversarial attacks, which are mostly input-specific in nature. Recently, it has been shown that there also exist in…

cs.CL20215 cited

Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events

Le Fang, Tao Zeng, Chaochun Liu +3

Large-scale pretrained language models have shown thrilling generation capabilities, especially when they generate consistent long text in thousands of words with ease. However, us…

cs.CL2021

SDA: Improving Text Generation with Self Data Augmentation

Ping Yu, Ruiyi Zhang, Yang Zhao +3

Data augmentation has been widely used to improve deep neural networks in many research fields, such as computer vision. However, less work has been done in the context of text, pa…