17 citations · 28 across the 6 of their papers we have counts for
3 papers · 1 filter
Long Context RAG Performance of Large Language Models
Quinn Leng, Jacob Portes, Sam Havens +2
Retrieval Augmented Generation (RAG) has emerged as a crucial technique for enhancing the accuracy of Large Language Models (LLMs) by incorporating external information. With the a…
LoRA Learns Less and Forgets Less
Dan Biderman, Jacob Portes, Jose Javier Gonzalez Ortiz +9
Low-Rank Adaptation (LoRA) is a widely-used parameter-efficient finetuning method for large language models. LoRA saves memory by training only low rank perturbations to selected w…
LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms
Aditi Jha, Sam Havens, Jeremy Dohmann +2
Large Language Models are traditionally finetuned on large instruction datasets. However recent studies suggest that small, high-quality datasets can suffice for general purpose in…