3 papers
cs.CL2025
A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation
Neal Gregory Lawton, Alfy Samuel, Anoop Kumar +1
A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation Download PDF Neal Gregory Lawton, Alfy Samuel, Anoop Kumar, Daben Liu Published: 20…
cs.LG2024
Learning Morphisms with Gauss-Newton Approximation for Growing Networks
Neal Lawton, Aram Galstyan, Greg Ver Steeg
A popular method for Neural Architecture Search (NAS) is based on growing networks via small local changes to the network's architecture called network morphisms. These methods sta…
cs.LG2024
QuAILoRA: Quantization-Aware Initialization for LoRA
Neal Lawton, Aishwarya Padmakumar, Judith Gaspers +4
QLoRA reduces the memory-cost of fine-tuning a large language model (LLM) with LoRA by quantizing the base LLM. However, quantization introduces quantization errors that negatively…