You Do Not Fully Utilize Transformer's Representation Capacity Paper • 2502.09245 • Published 11 days ago • 30
You Do Not Fully Utilize Transformer's Representation Capacity Paper • 2502.09245 • Published 11 days ago • 30
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Paper • 2502.03032 • Published 19 days ago • 55
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Paper • 2502.03032 • Published 19 days ago • 55
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Paper • 2502.03032 • Published 19 days ago • 55 • 2
The Differences Between Direct Alignment Algorithms are a Blur Paper • 2502.01237 • Published 21 days ago • 111
The Differences Between Direct Alignment Algorithms are a Blur Paper • 2502.01237 • Published 21 days ago • 111
Mechanistic Permutability: Match Features Across Layers Paper • 2410.07656 • Published Oct 10, 2024 • 18
Mechanistic Permutability: Match Features Across Layers Paper • 2410.07656 • Published Oct 10, 2024 • 18 • 2
Mechanistic Permutability: Match Features Across Layers Paper • 2410.07656 • Published Oct 10, 2024 • 18
Classifiers are Better Experts for Controllable Text Generation Paper • 2205.07276 • Published May 15, 2022
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM Paper • 2406.12168 • Published Jun 18, 2024 • 7
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning Paper • 2406.08973 • Published Jun 13, 2024 • 87
Implicit Unlikelihood Training: Improving Neural Text Generation with Reinforcement Learning Paper • 2101.04229 • Published Jan 11, 2021
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Paper • 2403.03507 • Published Mar 6, 2024 • 185
Linear Transformers with Learnable Kernel Functions are Better In-Context Models Paper • 2402.10644 • Published Feb 16, 2024 • 80