DeepSeek challenged this assumption by skipping SFT entirely, opting instead to rely on reinforcement learning (RL) to train the model. This bold move forced DeepSeek-R1 to develop independent ...

“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...

Jeremy Corbel, in the final episode of UFO Revolution's second season, delivers a significant warning about potential deception in the UFO community. He emphasizes the importance of this message ...

Reinforcement learning is a subset of machine learning where agents learn to make decisions by interacting with their environment and receiving rewards or penalties based on their actions. Unlike ...

TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Proximal Policy Optimization (PPO), and Direct Preference ...

Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the ...

Rammed earth (RE) construction has gained increasing interest in recent years owing to sustainability demands in the construction industry and the advancement of digital fabrication techniques.