agentic-reasoning-for-large-language-models

name	agentic-reasoning-for-large-language-models
title	Agentic Reasoning for Large Language Models
version	0.0.2
engine	skillxiv-v0.0.2-claude-opus-4.6
license	MIT
url	https://arxiv.org/abs/2601.12538
keywords	["Agent","Reasoning"]
description	Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) demonstrate strong reasoning capabilities in closed-world settings, they struggle in open-ended and dynamic environments. Agentic reasoning marks a paradigm shift by reframing LLMs as autonomous agents that plan, act, and learn through continual interaction. In this survey, we organize agentic reasoning along three complementary dimensions. First, we charact...

Overview

This skill covers agentic reasoning for large language models. It addresses critical challenges in autonomous agent development.

Key Concepts

The paper introduces novel approaches to:

• Agent evaluation and benchmarking
• Improving agent efficiency and reasoning
• Designing robust agent systems

When to Use

Use this when working on:

• Agent-based systems and evaluation
• Autonomous reasoning and planning
• Multi-agent frameworks

When NOT to Use

• Non-agent applications
• Tasks requiring implementation code (see the paper)

References

• Paper: https://arxiv.org/abs/2601.12538
• PDF: https://arxiv.org/pdf/2601.12538