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Vintix II: Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner

Vintix II demonstrates that transformer models can perform reinforcement learning purely through in-context adaptation, eliminating fine-tuning and enabling scalable adaptive agents.

Wednesday, April 8, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline

Vintix II presents a decision pre-trained transformer architecture designed for in-context reinforcement learning. The model enables RL agents to adapt from experience within context windows, focusing on scalability properties without requiring fine-tuning.

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