This AI Paper Introduces WINGS: A Dual-Learner Architecture to Prevent Text-Only Forgetting in Multimodal Large Language Models
Source: MarkTechPost Multimodal LLMs: Expanding Capabilities Across Text and Vision Expanding large language models (LLMs) to handle multiple...
Mistral AI Releases Mistral Small 3.2: Enhanced Instruction Following, Reduced Repetition, and Stronger Function Calling for AI Integration
Source: MarkTechPost With the frequent release of new large language models (LLMs), there is a persistent quest to...
Why Generalization in Flow Matching Models Comes from Approximation, Not Stochasticity
Source: MarkTechPost Introduction: Understanding Generalization in Deep Generative Models Deep generative models, including diffusion and flow matching, have...
Meta AI Researchers Introduced a Scalable Byte-Level Autoregressive U-Net Model That Outperforms Token-Based Transformers Across Language Modeling Benchmarks
Source: MarkTechPost Language modeling plays a foundational role in natural language processing, enabling machines to predict and generate...
This AI Paper from Google Introduces a Causal Framework to Interpret Subgroup Fairness in Machine Learning Evaluations More Reliably
Source: MarkTechPost Understanding Subgroup Fairness in Machine Learning ML Evaluating fairness in machine learning often involves examining how...
MiniMax AI Releases MiniMax-M1: A 456B Parameter Hybrid Model for Long-Context and Reinforcement Learning RL Tasks
Source: MarkTechPost The Challenge of Long-Context Reasoning in AI Models Large reasoning models are not only designed to...
ReVisual-R1: An Open-Source 7B Multimodal Large Language Model (MLLMs) that Achieves Long, Accurate and Thoughtful Reasoning
Source: MarkTechPost The Challenge of Multimodal Reasoning Recent breakthroughs in text-based language models, such as DeepSeek-R1, have demonstrated...
HtFLlib: A Unified Benchmarking Library for Evaluating Heterogeneous Federated Learning Methods Across Modalities
Source: MarkTechPost AI institutions develop heterogeneous models for specific tasks but face data scarcity challenges during training. Traditional...
How Latent Vector Fields Reveal the Inner Workings of Neural Autoencoders
Source: MarkTechPost Autoencoders and the Latent Space Neural networks are designed to learn compressed representations of high-dimensional data,...
AREAL: Accelerating Large Reasoning Model Training with Fully Asynchronous Reinforcement Learning
Source: MarkTechPost Introduction: The Need for Efficient RL in LRMs Reinforcement Learning RL is increasingly used to enhance...