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Solar dominates Africa’s energy investments, but millions remain in the dark

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Meta AI’s Llama Language Model modded to run in old Xbox...

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OpenAI presents a new blueprint for AI regulation that is its...

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Sa2VA: A Unified AI Framework for Dense Grounded Video and Image...

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Natural Language Processing

What are Small Language Models (SLMs)?

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This AI Paper Introduces Toto: Autoregressive Video Models for Unified Image...

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R3GAN: A Simplified and Stable Baseline for Generative Adversarial Networks GANs

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Researchers from Fudan University and Shanghai AI Lab Introduces DOLPHIN: A...

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Meta AI Introduces CLUE (Constitutional MLLM JUdgE): An AI Framework Designed...

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Salesforce AI Introduces TACO: A New Family of Multimodal Action Models...

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Can LLMs Really Judge with Reasoning? Microsoft and Tsinghua Researchers Introduce...

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Evaluating potential cybersecurity threats of advanced AI

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Taking a responsible path to AGI

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DolphinGemma: How Google AI is helping decode dolphin communication

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Can LLMs Really Judge with Reasoning? Microsoft and Tsinghua Researchers Introduce...

Reinforcement learning (RL) has emerged as a fundamental approach in LLM post-training, utilizing supervision signals from human feedback (RLHF) or verifiable rewards (RLVR). While RLVR shows promise in mathematical reasoning, it faces significant constraints due to dependence on training queries with verifiable answers. This requirement limits applications to large-scale...