autotrust/JEV-27B: fast, calibrated decisions and full reasoning from one open model autotrust • 12 days ago • 218
autotrust/JEV-27B-VL: a decision model that learned to see without a single image of training autotrust • 9 days ago • 165
NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular Prediction nvidia • 9 days ago • 86
Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs allenai • 7 days ago • 25
LightOnOCR-3: High-Performance OCR and Layout Extraction in One Model lightonai • about 6 hours ago • 16
Darwin-27B-ZTC: A Single-Pass Judge and a Quantitative Look at Its Calibration FINAL-Bench • about 14 hours ago • 12
Live Human Feedback in the Training Loop: Aligning Diffusion Models with Real People Rapidata • 6 days ago • 10
YODAS v3: A 1 Million Hour Dataset for the Next Generation of Open Voice AI Research espnet • 11 days ago • 34
How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows nvidia • 15 days ago • 56
autotrust/JEV-27B: fast, calibrated decisions and full reasoning from one open model autotrust • 12 days ago • 218
autotrust/JEV-27B-VL: a decision model that learned to see without a single image of training autotrust • 9 days ago • 165
NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular Prediction nvidia • 9 days ago • 86
Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs allenai • 7 days ago • 25
LightOnOCR-3: High-Performance OCR and Layout Extraction in One Model lightonai • about 6 hours ago • 16
Darwin-27B-ZTC: A Single-Pass Judge and a Quantitative Look at Its Calibration FINAL-Bench • about 14 hours ago • 12
Live Human Feedback in the Training Loop: Aligning Diffusion Models with Real People Rapidata • 6 days ago • 10
YODAS v3: A 1 Million Hour Dataset for the Next Generation of Open Voice AI Research espnet • 11 days ago • 34
How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows nvidia • 15 days ago • 56