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NVIDIA Introduces ProRL: Long-Horizon Reinforcement Learning Boosts Reasoning and Generalization

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RL^V: Unifying Reasoning and Verification in Language Models through Value-Free Reinforcement...

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Reinforcement Learning, Not Fine-Tuning: Nemotron-Tool-N1 Trains LLMs to Use Tools with...

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PrimeIntellect Releases INTELLECT-2: A 32B Reasoning Model Trained via Distributed Asynchronous...

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Microsoft Researchers Introduce ARTIST: A Reinforcement Learning Framework That Equips LLMs...

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ZeroSearch from Alibaba Uses Reinforcement Learning and Simulated Documents to Teach...

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You can now fine-tune your enterprise’s own version of OpenAI’s o4-mini...

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Scaling Up Reinforcement Learning for Traffic Smoothing: A 100-AV Highway Deployment

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Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning

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Hidden costs of AI deployment: Why Claude model may be 20-30%...

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World Emulation via Neural Network (

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NVIDIA Introduces ProRL: Long-Horizon Reinforcement Learning Boosts Reasoning and Generalization

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Top Artificial Intelligence AI Books to Read in 2025

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Salesforce AI Introduces CRMArena-Pro: The First Multi-Turn and Enterprise-Grade Benchmark for...

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From Clicking to Reasoning: WebChoreArena Benchmark Challenges Agents with Memory-Heavy and...

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NVIDIA Introduces ProRL: Long-Horizon Reinforcement Learning Boosts Reasoning and Generalization

Recent advances in reasoning-focused language models have marked a major change in AI by scaling test-time computation. Reinforcement learning (RL) is crucial in developing reasoning capabilities and mitigating reward hacking pitfalls. However, a fundamental debate remains: whether RL provides new reasoning capabilities from a base model or just helps...