✨TiDAR: Think in Diffusion, Talk in Autoregression

📝 Summary:
TiDAR is a hybrid diffusion-autoregressive model achieving high throughput and AR-level quality. It drafts tokens with diffusion and samples autoregressively in a single pass, outperforming existing methods and delivering 4.71x to 5.91x faster generation.

🔹 Publication Date: Published on Nov 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.08923
• PDF: https://arxiv.org/pdf/2511.08923

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#AI #MachineLearning #DiffusionModels #AutoregressiveModels #GenerativeAI

✨Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning

📝 Summary:
AR models face inefficient exploration and sparse rewards in RL. Internal RL uses a higher-order model to learn temporal abstraction controllers. This enables efficient learning from sparse rewards where standard RL fails.

🔹 Publication Date: Published on Dec 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.20605
• PDF: https://arxiv.org/pdf/2512.20605

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✓ https://t.me/DataScienceT

#ReinforcementLearning #HierarchicalRL #AutoregressiveModels #MachineLearning #ArtificialIntelligence