2 papers
cs.CL2026
Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs
Mingyu Lee, Akshat Ramachandran, Souvik Kundu +1
The inference efficiency of diffusion large language models (dLLMs) is constrained by two challenges: bidirectional attention precludes efficient KV-cache reuse, while increasing d…
cs.CV2025
OuroMamba: A Data-Free Quantization Framework for Vision Mamba
Akshat Ramachandran, Mingyu Lee, Huan Xu +2
We present OuroMamba, the first data-free post-training quantization (DFQ) method for vision Mamba-based models (VMMs). We identify two key challenges in enabling DFQ for VMMs, (1)…