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RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 31 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127 -
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Paper • 2412.12098 • Published • 4
Collections
Discover the best community collections!
Collections including paper arxiv:2503.19385
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Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation
Paper • 2502.20388 • Published • 16 -
Long-Context Autoregressive Video Modeling with Next-Frame Prediction
Paper • 2503.19325 • Published • 73 -
Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing
Paper • 2503.19385 • Published • 34 -
Packing Input Frame Context in Next-Frame Prediction Models for Video Generation
Paper • 2504.12626 • Published • 52
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Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Paper • 2401.09048 • Published • 10 -
Improving fine-grained understanding in image-text pre-training
Paper • 2401.09865 • Published • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78
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Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Paper • 2401.09048 • Published • 10 -
Improving fine-grained understanding in image-text pre-training
Paper • 2401.09865 • Published • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78
-
RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 31 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127 -
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Paper • 2412.12098 • Published • 4
-
RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 31 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127 -
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Paper • 2412.12098 • Published • 4
-
Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Paper • 2401.09048 • Published • 10 -
Improving fine-grained understanding in image-text pre-training
Paper • 2401.09865 • Published • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78
-
Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation
Paper • 2502.20388 • Published • 16 -
Long-Context Autoregressive Video Modeling with Next-Frame Prediction
Paper • 2503.19325 • Published • 73 -
Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing
Paper • 2503.19385 • Published • 34 -
Packing Input Frame Context in Next-Frame Prediction Models for Video Generation
Paper • 2504.12626 • Published • 52
-
RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 31 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127 -
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Paper • 2412.12098 • Published • 4
-
Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Paper • 2401.09048 • Published • 10 -
Improving fine-grained understanding in image-text pre-training
Paper • 2401.09865 • Published • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78