2 citations · 4 across the 13 of their papers we have counts for
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FlashMask-3: Efficient and Expressive Mask-Aware Distributed Attention
Guoxia Wang, Qianyue He, Siming Wu +6
Long-context training of large language and multimodal models couples structured attention masks (document, prefix-LM, share-question, sliding-window, block-sparse) with multi-node…
Sparse Layer Sharpness-Aware Minimization for Efficient Fine-Tuning
Yifei Cheng, Xianglin Yang, Guoxia Wang +5
Sharpness-aware minimization (SAM) seeks the minima with a flat loss landscape to improve the generalization performance in machine learning tasks, including fine-tuning. However,…
Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities
Zhiwei Hao, Jianyuan Guo, Li Shen +6
Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for their training present a signific…
SeWA: Selective Weight Average via Probabilistic Masking
Peng Wang, Shengchao Hu, Zerui Tao +5
Weight averaging has become a standard technique for enhancing model performance. However, methods such as Stochastic Weight Averaging (SWA) and Latest Weight Averaging (LAWA) ofte…
AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping
Guoxia Wang, Shuai Li, Congliang Chen +5
Loss spikes remain a persistent obstacle in large-scale language model pretraining. While previous research has attempted to identify the root cause of loss spikes by investigating…
FlashMask: Efficient and Rich Mask Extension of FlashAttention
Guoxia Wang, Jinle Zeng, Xiyuan Xiao +7
The computational and memory demands of vanilla attention scale quadratically with the sequence length , posing significant challenges for processing long sequences in Transform…