14 citations · 44 across the 10 of their papers we have counts for
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cs.CL2021★ 5 cited
Magic Pyramid: Accelerating Inference with Early Exiting and Token Pruning
Xuanli He, Iman Keivanloo, Yi Xu +4
Pre-training and then fine-tuning large language models is commonly used to achieve state-of-the-art performance in natural language processing (NLP) tasks. However, most pre-train…
cs.CL2021★ 2 cited
Dialogue-oriented Pre-training
Yi Xu, Hai Zhao
Pre-trained language models (PrLM) has been shown powerful in enhancing a broad range of downstream tasks including various dialogue related ones. However, PrLMs are usually traine…
stat.ML2021★ 9 cited
Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE
Junya Chen, Zhe Gan, Xuan Li +10
InfoNCE-based contrastive representation learners, such as SimCLR, have been tremendously successful in recent years. However, these contrastive schemes are notoriously resource de…