MixtureVitae: Open Web-Scale Pretraining Dataset With High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources Paper • 2509.25531 • Published Sep 29 • 7
MixtureVitae: Open Web-Scale Pretraining Dataset With High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources Paper • 2509.25531 • Published Sep 29 • 7
MixtureVitae: Open Web-Scale Pretraining Dataset With High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources Paper • 2509.25531 • Published Sep 29 • 7
MixtureVitae: Open Web-Scale Pretraining Dataset With High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources Paper • 2509.25531 • Published Sep 29 • 7
Optimal Sparsity of Mixture-of-Experts Language Models for Reasoning Tasks Paper • 2508.18672 • Published Aug 26 • 10
mSCoRe: a $M$ultilingual and Scalable Benchmark for $S$kill-based $Co$mmonsense $Re$asoning Paper • 2508.10137 • Published Aug 13 • 2
Lizard: An Efficient Linearization Framework for Large Language Models Paper • 2507.09025 • Published Jul 11 • 18
SLR: An Automated Synthesis Framework for Scalable Logical Reasoning Paper • 2506.15787 • Published Jun 18 • 2
How to Train your Text-to-Image Model: Evaluating Design Choices for Synthetic Training Captions Paper • 2506.16679 • Published Jun 20 • 1
Self-Correction Bench: Revealing and Addressing the Self-Correction Blind Spot in LLMs Paper • 2507.02778 • Published Jul 3 • 9
Rewriting Pre-Training Data Boosts LLM Performance in Math and Code Paper • 2505.02881 • Published May 5 • 4
EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition Paper • 2505.20033 • Published May 26 • 4
EmoNet-Voice: A Fine-Grained, Expert-Verified Benchmark for Speech Emotion Detection Paper • 2506.09827 • Published Jun 11 • 20