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MiroMind-M1: Advancing Open-Source Mathematical Reasoning via Context-Aware Multi-Stage Reinforcement Learning
Large language models (LLMs) have recently demonstrated remarkable progress in multi-step reasoning, establishing mathematical problem-solving...
Mira Murati’s Thinking Machines Lab Introduces Interaction Models: A Native Multimodal Architecture for Real-Time Human-AI Collaboration
Most AI systems today work in turns. You type or speak, the model waits, processes...
MinosEval: Distinguishing Factoid and Non-Factoid for Tailored Open-Ended QA Evaluation with LLMs
arXiv:2506.15215v1 Announce Type: new Abstract: Open-ended question answering (QA) is a key task for evaluating...
MiniMax Sparse Attention (MSA): a Two-Branch Block-Sparse Attention Trained on a 109B-Parameter MoE With a 3T-Token Budget
MiniMax released MSA (MiniMax Sparse Attention), a sparse attention method built directly on Grouped Query...
MiniMax Releases MiniMax-Music3: An Open-Weights Music Model Generating Complete Five-Minute Songs From Lyrics and a Structured Caption
MiniMax released MiniMax-Music3, an open-weights text-to-music model. The model takes two separate inputs: lyrics carrying...
MiniMax Releases MiniMax H3: An Omni-Modal Video Model That Generates 15-Second 2K Clips With Native Stereo Audio
MiniMax releases MiniMax H3, a general-purpose multimodal generation model. MiniMax H3 is not a text-to-video...
MiniMax Releases M2.1: An Enhanced M2 Version with Features like Multi-Coding Language Support, API Integration, and Improved Tools for Structured Coding
Just months after releasing M2—a fast, low-cost model designed for agents and code—MiniMax has introduced...
MiniMax AI Releases MiniMax-M1: A 456B Parameter Hybrid Model for Long-Context and Reinforcement Learning RL Tasks
The Challenge of Long-Context Reasoning in AI Models Large reasoning models are not only designed...
Mind-altering substances are (still) falling short in clinical trials
This week I want to look at where we are with psychedelics, the mind-altering substances...
Mind Your Moras: Orthography-Aware Error Analysis of Neural Japanese Morphological Generation
arXiv:2605.20043v2 Announce Type: replace Abstract: We present an orthography-aware error analysis of Japanese past-tense morphological...
Mind the Gap: A Review of Arabic Post-Training Datasets and Their Limitations
arXiv:2507.14688v1 Announce Type: new Abstract: Post-training has emerged as a crucial technique for aligning pre-trained...
Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning
arXiv:2508.21589v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) Large Language Models (LLM) fundamentally rely on...
