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Shuai Pang

2 accepted papers

2025

Scaling and Taming Adversarial Training with Synthetic Data

ICCV 2025poster

Despite the success of adversarial training on small datasets, applying it to large-scale datasets like ImageNet remains challenging. Previous attempts using synthetic data show limited improvements. This work investigates the impact of synthetic data scaling, model scaling, and training strategies…

Cited by 0SourcePDFScholar
2020

FASTMATCH: Accelerating the Inference of BERT-based Text Matching

COLING 2020main

Recently, pre-trained language models such as BERT have shown state-of-the-art accuracies in text matching. When being applied to IR (or QA), the BERT-based matching models need to online calculate the representations and interactions for all query-candidate pairs. The high inference cost has prohib…

Cited by 4SourcePDFScholar