#reasoning

'NVIDIA's Reinforcement Learning Pretraining (RLP) injects dense, position-wise reinforcement into pretraining by rewarding chains-of-thought for information gain, improving reasoning and data efficiency across architectures.'

ByteDance researchers introduce ProtoReasoning, a new framework leveraging logic-based prototypes to significantly improve reasoning and planning abilities in large language models across various domains.

Tool-augmented AI agents enhance language models by integrating reasoning, memory, and autonomous capabilities, enabling smarter and more reliable AI systems.

Researchers improve large language models' reasoning by explicitly aligning core abilities like deduction, induction, and abduction, surpassing traditional instruction-tuned models in accuracy and reliability.