T-Tech

T-Tech on Hugging Face Daily Papers: 17 papers, 7 in the top 3 of their day, 5 paper of the day.

  1. From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix 35 upvotes, #8 of 2026-09-02
  2. Rank-Then-Act: Reward-Free Control from Frame-Order Progress 7 upvotes, #25 of 2026-07-08
  3. Unstable Features, Reproducible Subspaces: Understanding Seed Dependence in Sparse Autoencoders 8 upvotes, #28 of 2026-06-16
  4. Interpreting and Steering a Text-to-Speech Language Model with Sparse Autoencoders 12 upvotes, #19 of 2026-06-10
  5. Trust-Region Behavior Blending for On-Policy Distillation 65 upvotes, #3 of 2026-06-01
  6. Next Embedding Prediction Makes World Models Stronger 17 upvotes, #11 of 2026-03-04
  7. F-GRPO: Don't Let Your Policy Learn the Obvious and Forget the Rare 70 upvotes, #1 of 2026-02-09
  8. T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground 83 upvotes, #1 of 2025-12-12
  9. Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success 34 upvotes, #7 of 2025-08-07
  10. Teach Old SAEs New Domain Tricks with Boosting 11 upvotes, #12 of 2025-07-18
  11. Train Sparse Autoencoders Efficiently by Utilizing Features Correlation 21 upvotes, #16 of 2025-05-30
  12. You Do Not Fully Utilize Transformer's Representation Capacity 33 upvotes, #8 of 2025-02-19
  13. Analyze Feature Flow to Enhance Interpretation and Steering in Language Models 53 upvotes, #1 of 2025-02-07
  14. The Differences Between Direct Alignment Algorithms are a Blur 109 upvotes, #2 of 2025-02-04
  15. Mechanistic Permutability: Match Features Across Layers 16 upvotes, #7 of 2024-10-14
  16. Learn Your Reference Model for Real Good Alignment 75 upvotes, #1 of 2024-04-16
  17. Linear Transformers with Learnable Kernel Functions are Better In-Context Models 81 upvotes, #1 of 2024-02-19

Data: hysts-bot-data/daily-papers-stats and the Daily Papers API. Open data: tardellirs/paper-pulse-data. Sister project: Model Pulse, the download history of every model on the Hub.