The Generative AI Paradox: "What It Can Create, It May Not Understand" Paper • 2311.00059 • Published Oct 31, 2023 • 18
Teaching Large Language Models to Reason with Reinforcement Learning Paper • 2403.04642 • Published Mar 7 • 46
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM Paper • 2403.07816 • Published Mar 12 • 38
PERL: Parameter Efficient Reinforcement Learning from Human Feedback Paper • 2403.10704 • Published Mar 15 • 56
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement Paper • 2403.15042 • Published Mar 22 • 24
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text Paper • 2403.18421 • Published Mar 27 • 21
Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model Paper • 2404.04167 • Published Apr 5 • 11
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies Paper • 2404.06395 • Published Apr 9 • 19
OpenBezoar: Small, Cost-Effective and Open Models Trained on Mixes of Instruction Data Paper • 2404.12195 • Published Apr 18 • 11
MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series Paper • 2405.19327 • Published May 29 • 43