5 papers · 1 filter
Accelerate Speculative Decoding with Sparse Computation in Verification
Jikai Wang, Jianchao Tan, Yuxuan Hu +6
Speculative decoding accelerates autoregressive language model inference by verifying multiple draft tokens in parallel. However, the verification stage often becomes the dominant…
Optimizing Native Sparse Attention with Latent Attention and Local Global Alternating Strategies
Yuxuan Hu, Jianchao Tan, Jiaqi Zhang +7
In this work, we conduct a systematic analysis of Native Sparse Attention (NSA) and propose targeted improvements that enhance long-context modeling. A key insight is that alternat…
WISCA: A Lightweight Model Transition Method to Improve LLM Training via Weight Scaling
Jiacheng Li, Jianchao Tan, Zhidong Yang +11
Transformer architecture gradually dominates the LLM field. Recent advances in training optimization for Transformer-based large language models (LLMs) primarily focus on architect…
MaskPrune: Mask-based LLM Pruning for Layer-wise Uniform Structures
Jiayu Qin, Jianchao Tan, Kefeng Zhang +2
The remarkable performance of large language models (LLMs) in various language tasks has attracted considerable attention. However, the ever-increasing size of these models present…
C2T: A Classifier-Based Tree Construction Method in Speculative Decoding
Feiye Huo, Jianchao Tan, Kefeng Zhang +2
The growing scale of Large Language Models (LLMs) has exacerbated inference latency and computational costs. Speculative decoding methods, which aim to mitigate these issues, often…