SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond Paper • 2505.19641 • Published 11 days ago • 64
One-RL-to-See-Them-All Collection https://github.com/MiniMax-AI/One-RL-to-See-Them-All • 5 items • Updated 11 days ago • 12
Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention Paper • 2405.17381 • Published May 27, 2024
MiniMax-01: Scaling Foundation Models with Lightning Attention Paper • 2501.08313 • Published Jan 14 • 293
You Only Scan Once: Efficient Multi-dimension Sequential Modeling with LightNet Paper • 2405.21022 • Published May 31, 2024
One RL to See Them All: Visual Triple Unified Reinforcement Learning Paper • 2505.18129 • Published 14 days ago • 59
One RL to See Them All: Visual Triple Unified Reinforcement Learning Paper • 2505.18129 • Published 14 days ago • 59
One RL to See Them All: Visual Triple Unified Reinforcement Learning Paper • 2505.18129 • Published 14 days ago • 59 • 2
MiniMax-Speech: Intrinsic Zero-Shot Text-to-Speech with a Learnable Speaker Encoder Paper • 2505.07916 • Published 25 days ago • 124
Rethinking RL Scaling for Vision Language Models: A Transparent, From-Scratch Framework and Comprehensive Evaluation Scheme Paper • 2504.02587 • Published Apr 3 • 30
Rethinking RL Scaling for Vision Language Models: A Transparent, From-Scratch Framework and Comprehensive Evaluation Scheme Paper • 2504.02587 • Published Apr 3 • 30
MiniMax-01: Scaling Foundation Models with Lightning Attention Paper • 2501.08313 • Published Jan 14 • 293
MiniMax-01: Scaling Foundation Models with Lightning Attention Paper • 2501.08313 • Published Jan 14 • 293 • 6