8 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Which Quantization Should I Use? A Unified Evaluation of llama.cpp Quantization on Llama-3.1-8B-Instruct
Uygar Kurt
Quantization is a practical technique for making large language models easier to deploy by reducing the precision used to store and operate on model weights. This can lower memory…
cs.CL2024★ 8 cited
CompactifAI: Extreme Compression of Large Language Models using Quantum-Inspired Tensor Networks
Andrei Tomut, Saeed S. Jahromi, Abhijoy Sarkar +15
Large Language Models (LLMs) such as ChatGPT and LlaMA are advancing rapidly in generative Artificial Intelligence (AI), but their immense size poses significant challenges, such a…
cs.CY2022
Keywords for Bias
Abdurrezak Efe, Gizem Gezici, Aysenur Uzun +1
This work proposes to analyse some keywords for bias analysis. For this, we are using several NLP approaches and compare them based on their capability of detecting keywords to ana…