Nachrichten
Miso Labs Releases MisoTTS: An 8B Emotive Text-to-Speech Model with Open Weights
Miso Labs has released MisoTTS, an open-weights 8-billion-parameter text-to-speech model. It generates expressive speech from...
MiroMind-M1: An Open-Source Advancement in Mathematical Reasoning via Context-Aware Multi-Stage Policy Optimization
arXiv:2507.14683v1 Announce Type: new Abstract: Large language models have recently evolved from fluent text generation...
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 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...
