autotrust/JEV-27B-VL: a decision model that learned to see without a single image of training autotrust • 11 days ago • 126
autotrust/JEV-27B: fast, calibrated decisions and full reasoning from one open model autotrust • 14 days ago • 47
NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular Prediction nvidia • 12 days ago • 89
Darwin-27B-ZTC: A Single-Pass Judge and a Quantitative Look at Its Calibration FINAL-Bench • 3 days ago • 12
The Open Quantum Challenge: Quantum Simulation and QEC Decoding on Classical GPUs FINAL-Bench • about 8 hours ago • 9
Leading the System One Mosaic Benchmark: What Darwin-27B-ZTC-v2's #1 Means FINAL-Bench • 2 days ago • 6
ViDiHand: The Surprising Effectiveness of Video Diffusion Models for Hand Motion Reconstruction Xingang-Pan • 5 days ago • 4
YODAS v3: A 1 Million Hour Dataset for the Next Generation of Open Voice AI Research espnet • 14 days ago • 36
autotrust/JEV-27B-VL: a decision model that learned to see without a single image of training autotrust • 11 days ago • 126
autotrust/JEV-27B: fast, calibrated decisions and full reasoning from one open model autotrust • 14 days ago • 47
NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular Prediction nvidia • 12 days ago • 89
Darwin-27B-ZTC: A Single-Pass Judge and a Quantitative Look at Its Calibration FINAL-Bench • 3 days ago • 12
The Open Quantum Challenge: Quantum Simulation and QEC Decoding on Classical GPUs FINAL-Bench • about 8 hours ago • 9
Leading the System One Mosaic Benchmark: What Darwin-27B-ZTC-v2's #1 Means FINAL-Bench • 2 days ago • 6
ViDiHand: The Surprising Effectiveness of Video Diffusion Models for Hand Motion Reconstruction Xingang-Pan • 5 days ago • 4
YODAS v3: A 1 Million Hour Dataset for the Next Generation of Open Voice AI Research espnet • 14 days ago • 36