Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models Paper • 2503.24377 • Published 5 days ago • 16
M-STAR Collection Resources of M-STAR (Multimodal Self-Evolving Training for Reasoning) https://mstar-lmm.github.io/ • 2 items • Updated Dec 25, 2024 • 4
SimpleRL Collection The collection for the Project "Simple Reinforcement Learning for Reasoning" • 2 items • Updated Feb 19 • 6
SimpleRL-Zoo Collection The collection for the Paper "SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild" • 12 items • Updated 4 days ago • 6
SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild Paper • 2503.18892 • Published 12 days ago • 27
Language Models can Self-Improve at State-Value Estimation for Better Search Paper • 2503.02878 • Published Mar 4 • 9
Predictive Data Selection: The Data That Predicts Is the Data That Teaches Paper • 2503.00808 • Published Mar 2 • 56
LASP-2: Rethinking Sequence Parallelism for Linear Attention and Its Hybrid Paper • 2502.07563 • Published Feb 11 • 24
CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction Paper • 2502.07316 • Published Feb 11 • 47 • 3
CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction Paper • 2502.07316 • Published Feb 11 • 47
Test-Time Preference Optimization: On-the-Fly Alignment via Iterative Textual Feedback Paper • 2501.12895 • Published Jan 22 • 59