Academic Resource Collection
3.6k 2026-04-18

atfortes/Awesome-LLM-Reasoning

A comprehensive, curated collection of research papers and resources focused on enhancing and understanding the reasoning abilities of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs).

Core Features

Curated list of cutting-edge research papers on LLM/MLLM reasoning.
Categorized by topic (Survey, Analysis, Technique) and publication year.
Includes direct links to arXiv papers and associated code repositories.
Covers various aspects like Chain-of-Thought, multimodal reasoning, and scaling smaller LMs.
A valuable hub for researchers and practitioners in AI and natural language processing.

Detailed Introduction

Awesome LLM Reasoning is an invaluable academic resource hub meticulously curating a vast collection of papers and materials dedicated to exploring and advancing the reasoning capabilities of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs). It provides a structured overview of the latest research, from foundational Chain-of-Thought prompting to advanced techniques and analyses. This project serves as a critical reference for researchers, developers, and enthusiasts seeking to understand, implement, and push the boundaries of AI reasoning.

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