Papers by Ji-Fu Li
Benchmarking Post-Training Quantization of Large Language Models under Microscaling Floating Point Formats (2026.acl-long)
Copied to clipboard
| Challenge: | Microscaling Floating-Point (MXFP) is a low-precision format for large language models (LLMs). |
| Approach: | They conduct systematic evaluations of PTQ under Microscaling Floating-Point (MXFP) . they find that MXFP8 consistently achieves near-lossless performance . |
| Outcome: | The proposed method achieves near-lossless performance while MXFP4 introduces substantial accuracy degradation and remains challenging. |