7. Training LLMs with Reasoning Traces Ivestigates how reasoning traces from frontier models like DeepSeek-R1 and GPT-OSS can improve smaller language models through post-training.
MACHINE LEARNING
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Evolution Strategies Enable Backprop-Free Optimization Billion-Parameter Networks
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6. Evolution Strategies at Hyperscale An evolution strategies algorithm designed to scale backprop-free optimization to large population sizes for billion-parameter neural networks.
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LatentMAS: Language Model Agents Collaborate in Latent Space
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3. LatentMAS LatentMAS introduces a framework enabling language model agents to collaborate directly within a continuous latent space rather than relying on text-based communication.
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HunyuanOCR: Lightweight 1B Parameter Vision-Language Model
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2. Lightweight End-to-End OCR HunyuanOCR is a commercial-grade, open-source, lightweight vision-language model with only 1B parameters designed specifically for OCR tasks.
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INTELLECT-3: 106B MoE Model Achieves State-of-the-Art Performance
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1. INTELLECT-3
— DAIR.AI (@dair_ai) 30 novembre 2025
A 106B-parameter Mixture-of-Experts model (12B active) trained with large-scale reinforcement learning, achieving state-of-the-art performance for its size across math, code, science, and reasoning benchmarks.https://t.co/8tphkxnVzy1. INTELLECT-3 A 106B-parameter Mixture-of-Experts model (12B active) trained with large-scale reinforcement learning, achieving state-of-the-art performance for its size across math, code, science, and reasoning benchmarks.
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Top AI Papers of the Week: Latest Research Highlights
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Top AI Papers of the Week (Nov 24 – 30): – LatentMAS
– INTELLECT-3
– OmniScientist
– Lightweight End-to-End OCR
– Evolution Strategies at Hyperscale
– Training LLMs with Reasoning Traces
– Cognitive Foundations for Reasoning in LLMs Read on for more: -
Agentic AI Architecture Overview by Python Developer
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#AgenticAI Architecture by @Python_Dv #AI #GenAI #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning
→ View original post on X — @marcusborba, 2025-11-30 14:11 UTC
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Swarm Intelligence: The Collective Learning Secret Revealed
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Swarm intelligence has a secret. The standard approach treats swarms as collections of independent learners. Each agent makes decisions, learns from outcomes, and coordination somehow emerges. More agents, more complexity, more mystery. But what if the swarm itself is the
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VQ-Insight: Progressive Learning for AI Video Quality Evaluation
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How do we fix the messy state of AI video quality evaluation? Enter VQ-Insight: it uses progressive learning (starting with image quality, then adding temporal skills, and linking directly to generation models) plus multi-layered rewards to judge everything from frame
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Agentic AI and Explainable Models Drive Business Automation in 2025
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The rise of agentic AI and explainable models means smarter, transparent automation for businesses. AI and machine learning trends in 2025 https://
phaedrasolutions.com/blog/ai-and-ma
chine-learning-trends
… #AI #MachineLearning #IoT #DigitalTransformation