activity
20242026
most citedUnderstanding the Performance and Estimating the Cost of LLM Fine-Tuning

2 citations · 7 across the 15 of their papers we have counts for

collaborators
Showing cs.CVShow all

2 papers · 1 filter

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)…

cs.CV2024★ 1 cited

CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs

Akshat Ramachandran, Souvik Kundu, Tushar Krishna

We present CLAMP-ViT, a data-free post-training quantization method for vision transformers (ViTs). We identify the limitations of recent techniques, notably their inability to lev…