127 citations · 149 across the 10 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.LG2024★ 3 cited
Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs
Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang +10
The rise of large language models (LLMs) has created a significant disparity: industrial research labs with their computational resources, expert teams, and advanced infrastructure…
cs.CL2024★ 5 cited
LAB: Large-Scale Alignment for ChatBots
Shivchander Sudalairaj, Abhishek Bhandwaldar, Aldo Pareja +3
This work introduces LAB (Large-scale Alignment for chatBots), a novel methodology designed to overcome the scalability challenges in the instruction-tuning phase of large language…