3 citations · 3 across the 4 of their papers we have counts for
4 papers
NeuroPrefetcher: Storage-Aware Sparse LLM Inference via Delta Prefetching
Nobel Dhar, Md Romyull Islam, Xuechen Zhang +4
Deploying large language models on edge devices is increasingly limited by a widening gap between model size and available memory. Existing approaches such as quantization, smaller…
Characterizing and Understanding Energy Footprint and Efficiency of Small Language Model on Edges
Md Romyull Islam, Bobin Deng, Nobel Dhar +4
Cloud-based large language models (LLMs) and their variants have significantly influenced real-world applications. Deploying smaller models (i.e., small language models (SLMs)) on…
Activation Sparsity Opportunities for Compressing General Large Language Models
Nobel Dhar, Bobin Deng, Md Romyull Islam +3
Deploying local AI models, such as Large Language Models (LLMs), to edge devices can substantially enhance devices' independent capabilities, alleviate the server's burden, and low…
Pointer over Attention: An Improved Bangla Text Summarization Approach Using Hybrid Pointer Generator Network
Nobel Dhar, Gaurob Saha, Prithwiraj Bhattacharjee +2
Despite the success of the neural sequence-to-sequence model for abstractive text summarization, it has a few shortcomings, such as repeating inaccurate factual details and tending…