2 papers
cs.LG2026
ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs
Haoqian Meng, Yilun Luo, Yafei Zhao +3
The emergence of fine-grained numerical formats like NVFP4 presents new opportunities for efficient Large Language Model (LLM) inference. However, it is difficult to adapt existing…
cs.LG2026
SharQ: Bridging Activation Sparsity and FP4 Quantization for LLM Inference
Haoqian Meng, Yilun Luo, Yafei Zhao +4
Low-bit floating-point formats and semi-structured sparsity are increasingly supported by modern accelerators, yet combining them for LLM activation compression remains challenging…