Machine learning books and papers

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Paper submitted by #DeepSeek team has generated significant attention in the AI community.

This work addresses the enhancement of reasoning capabilities in Large Language Models (LLMs) through the application of reinforcement learning techniques. The authors introduce a novel framework, DeepSeek-R1, which aims to improve LLM reasoning abilities by incorporating incentives for logical reasoning processes within their training. This integration of reinforcement learning allows LLMs to go beyond basic linguistic processing, developing sophisticated reasoning methods that can boost performance across a wide array of complex applications.

This approach has cause lots of discussions in different communities, but it definitely opens up the whole new direction of development for the research.

Paper: https://arxiv.org/abs/2501.12948

#nn #LLM

@Machine_learn

arXiv.org

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via...

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...

❤2

www.tgoop.com/Machine_learn/3346

2.02K viewsJan 30 at 11:01

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Paper submitted by #DeepSeek team has generated significant attention in the AI community.

This work addresses the enhancement of reasoning capabilities in Large Language Models (LLMs) through the application of reinforcement learning techniques. The authors introduce a novel framework, DeepSeek-R1, which aims to improve LLM reasoning abilities by incorporating incentives for logical reasoning processes within their training. This integration of reinforcement learning allows LLMs to go beyond basic linguistic processing, developing sophisticated reasoning methods that can boost performance across a wide array of complex applications.

This approach has cause lots of discussions in different communities, but it definitely opens up the whole new direction of development for the research.

Paper: https://arxiv.org/abs/2501.12948

#nn #LLM

@Machine_learn

BY Machine learning books and papers