185 citations · 1.5k across the 88 of their papers we have counts for
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A Generic Approach for Enhancing GANs by Regularized Latent Optimization
Yufan Zhou, Chunyuan Li, Changyou Chen +1
With the rapidly growing model complexity and data volume, training deep generative models (DGMs) for better performance has becoming an increasingly more important challenge. Prev…
Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees
Yaman Kumar Singla, Sriram Krishna, Rajiv Ratn Shah +1
Automated Scoring (AS), the natural language processing task of scoring essays and speeches in an educational testing setting, is growing in popularity and being deployed across co…
LAFITE: Towards Language-Free Training for Text-to-Image Generation
Yufan Zhou, Ruiyi Zhang, Changyou Chen +6
One of the major challenges in training text-to-image generation models is the need of a large number of high-quality image-text pairs. While image samples are often easily accessi…
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…
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…
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…