most citedOh! We Freeze: Improving Quantized Knowledge Distillation via Signal Propagation Analysis for Large Language Models

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Video Reasoning without Training

Deepak Sridhar, Kartikeya Bhardwaj, Jeya Pradha Jeyaraj +3

Video reasoning using Large Multimodal Models (LMMs) relies on costly reinforcement learning (RL) and verbose chain-of-thought, resulting in substantial computational overhead duri…

cs.CV2025

SubZero: Composing Subject, Style, and Action via Zero-Shot Personalization

Shubhankar Borse, Kartikeya Bhardwaj, Mohammad Reza Karimi Dastjerdi +8

Diffusion models are increasingly popular for generative tasks, including personalized composition of subjects and styles. While diffusion models can generate user-specified subjec…

cs.LG2024

Rapid Switching and Multi-Adapter Fusion via Sparse High Rank Adapters

Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi +9

In this paper, we propose Sparse High Rank Adapters (SHiRA) that directly finetune 1-2% of the base model weights while leaving others unchanged, thus, resulting in a highly sparse…

cs.LG2024

Sparse High Rank Adapters

Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi +9

Low Rank Adaptation (LoRA) has gained massive attention in the recent generative AI research. One of the main advantages of LoRA is its ability to be fused with pretrained models,…

cs.LG20241 cited

Oh! We Freeze: Improving Quantized Knowledge Distillation via Signal Propagation Analysis for Large Language Models

Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi +3

Large generative models such as large language models (LLMs) and diffusion models have revolutionized the fields of NLP and computer vision respectively. However, their slow infere…