Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models Paper • 2409.17146 • Published Sep 25, 2024 • 104
OpenDevin: An Open Platform for AI Software Developers as Generalist Agents Paper • 2407.16741 • Published Jul 23, 2024 • 68
RegMix: Data Mixture as Regression for Language Model Pre-training Paper • 2407.01492 • Published Jul 1, 2024 • 35
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale Paper • 2406.17557 • Published Jun 25, 2024 • 87
From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models Paper • 2406.16838 • Published Jun 24, 2024 • 2
C-Pack: Packaged Resources To Advance General Chinese Embedding Paper • 2309.07597 • Published Sep 14, 2023 • 1
DataComp-LM: In search of the next generation of training sets for language models Paper • 2406.11794 • Published Jun 17, 2024 • 50
Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive? Paper • 2406.04391 • Published Jun 6, 2024 • 7
The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding Paper • 2406.02396 • Published Jun 4, 2024