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Agentic Reasoning For Large Language Models: Foundations Evolution Collaboration by varshinivky32 is a document available to read on EtoBox.

The document discusses agentic reasoning for large language models (LLMs), emphasizing their evolution from passive sequence generators to autonomous agents capable of planning, acting, and learning through interaction. It categorizes agentic reasoning into foundational capabilities, self-evolving adaptation, and collective intelligence, while distinguishing between in-context and post-training optimization modes. The survey also reviews real-world applications, benchmarks, and outlines future challenges in

Author

varshinivky32

Language

EN