Running Featured 20 Chasing the Counting Manifold in Open LLMs 📚 20 Counting manifolds in open LLMs from behavior to SAEs.
F-GRPO: Don't Let Your Policy Learn the Obvious and Forget the Rare Paper • 2602.06717 • Published 17 days ago • 71
F-GRPO: Don't Let Your Policy Learn the Obvious and Forget the Rare Paper • 2602.06717 • Published 17 days ago • 71
T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground Paper • 2512.10430 • Published Dec 11, 2025 • 115
ESSA: Evolutionary Strategies for Scalable Alignment Paper • 2507.04453 • Published Jul 6, 2025 • 5
ESSA: Evolutionary Strategies for Scalable Alignment Paper • 2507.04453 • Published Jul 6, 2025 • 5
The Differences Between Direct Alignment Algorithms are a Blur Paper • 2502.01237 • Published Feb 3, 2025 • 113 • 3
G-CUT3R: Guided 3D Reconstruction with Camera and Depth Prior Integration Paper • 2508.11379 • Published Aug 15, 2025 • 12
Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success Paper • 2508.04280 • Published Aug 6, 2025 • 35
Teach Old SAEs New Domain Tricks with Boosting Paper • 2507.12990 • Published Jul 17, 2025 • 12
Train Sparse Autoencoders Efficiently by Utilizing Features Correlation Paper • 2505.22255 • Published May 28, 2025 • 24
You Do Not Fully Utilize Transformer's Representation Capacity Paper • 2502.09245 • Published Feb 13, 2025 • 37
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Paper • 2502.03032 • Published Feb 5, 2025 • 60
The Differences Between Direct Alignment Algorithms are a Blur Paper • 2502.01237 • Published Feb 3, 2025 • 113
The Differences Between Direct Alignment Algorithms are a Blur Paper • 2502.01237 • Published Feb 3, 2025 • 113