The survey structures agentic reasoning for LLMs into foundational, self-evolving, and collective multi-agent layers while distinguishing in-context orchestration from post-training optimization and reviewing applications across domains.
Buffer of thoughts: Thought-augmented reasoning with large language models.Advances in Neural Information Processing Systems, 37:113519–113544
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Advanced language representations shape LLMs' schemas to improve knowledge activation and problem-solving.
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