3 papers
cs.CV2026
DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization
Haokun Lin, Xinle Jia, Haobo Xu +7
The MXFP4 microscaling format, which partitions tensors into blocks of 32 elements sharing an E8M0 scaling factor, has emerged as a promising substrate for efficient LLM inference,…
cs.CL2026
Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs
Haokun Lin, Haobo Xu, Yichen Wu +6
Recent advances in diffusion large language models (dLLMs) have introduced a promising alternative to autoregressive (AR) LLMs for natural language generation tasks, leveraging ful…
cs.CV2025
TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation
Haokun Lin, Teng Wang, Yixiao Ge +6
Pioneering token-based works such as Chameleon and Emu3 have established a foundation for multimodal unification but face challenges of high training computational overhead and lim…