G-CUT3R: Guided 3D Reconstruction with Camera and Depth Prior Integration Paper • 2508.11379 • Published Aug 15 • 12
Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success Paper • 2508.04280 • Published Aug 6 • 35
Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success Paper • 2508.04280 • Published Aug 6 • 35 • 2
Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success Paper • 2508.04280 • Published Aug 6 • 35
Train Sparse Autoencoders Efficiently by Utilizing Features Correlation Paper • 2505.22255 • Published May 28 • 24
Train Sparse Autoencoders Efficiently by Utilizing Features Correlation Paper • 2505.22255 • Published May 28 • 24
You Do Not Fully Utilize Transformer's Representation Capacity Paper • 2502.09245 • Published Feb 13 • 37
You Do Not Fully Utilize Transformer's Representation Capacity Paper • 2502.09245 • Published Feb 13 • 37
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Paper • 2502.03032 • Published Feb 5 • 60
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Paper • 2502.03032 • Published Feb 5 • 60
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Paper • 2502.03032 • Published Feb 5 • 60 • 2
The Differences Between Direct Alignment Algorithms are a Blur Paper • 2502.01237 • Published Feb 3 • 113
The Differences Between Direct Alignment Algorithms are a Blur Paper • 2502.01237 • Published Feb 3 • 113
Mechanistic Permutability: Match Features Across Layers Paper • 2410.07656 • Published Oct 10, 2024 • 20
Mechanistic Permutability: Match Features Across Layers Paper • 2410.07656 • Published Oct 10, 2024 • 20 • 2
Mechanistic Permutability: Match Features Across Layers Paper • 2410.07656 • Published Oct 10, 2024 • 20
Classifiers are Better Experts for Controllable Text Generation Paper • 2205.07276 • Published May 15, 2022