Distinguishing Learning Rules with Brain Machine Interfaces. - Jacob P. Portes; Christian Schmid; James M. Murray (NeurIPS, 2022)

Fast Benchmarking of Accuracy vs. Training Time with Cyclic Learning Rates. - Jacob P. Portes; Davis W. Blalock; Cory Stephenson; Jonathan Frankle (CoRR, 2022)

MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining. - Jacob P. Portes; Alexander Trott; Sam Havens; Daniel King; Abhinav Venigalla; Moin Nadeem; Nikhil Sardana; Daya Khudia; Jonathan Frankle (NeurIPS, 2023)

LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms. - Aditi Jha; Sam Havens; Jeremy Dohmann; Alex Trott; Jacob P. Portes (CoRR, 2023)

Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws. - Nikhil Sardana; Jacob P. Portes; Sasha Doubov; Jonathan Frankle (ICML, 2024)

Long Context RAG Performance of Large Language Models. - Quinn Leng; Jacob P. Portes; Sam Havens; Matei Zaharia; Michael Carbin (CoRR, 2024)

LoRA Learns Less and Forgets Less. - Dan Biderman; Jacob P. Portes; Jose Javier Gonzalez Ortiz; Mansheej Paul; Philip Greengard; Connor Jennings; Daniel King; Sam Havens; Vitaliy Chiley; Jonathan Frankle; Cody Blakeney; John Patrick Cunningham (Trans. Mach. Learn. Res., 2024)