Welcome to the Awesome LLMs Planning Reasoning repository! This collection is dedicated to exploring the rapidly evolving field of Large Language Models (LLMs) and their capabilities in planning and reasoning.
Overview
As LLMs continue to demonstrate remarkable success in Natural Language Understanding (NLU) and Natural Language Generation (NLG), researchers are increasingly interested in assessing their abilities beyond traditional NLP tasks. One of the most promising and challenging areas of study is understanding how well LLMs can perform tasks that require planning and reasoning. These capabilities are essential for leveraging LLMs in more complex, real-world scenarios, such as autonomous decision-making, problem-solving, and strategic thinking. However, recent research suggests that LLMs often struggle with reasoning tasks that are relatively simple for most humans, highlighting the limitations of these models in this critical area.
This repository is a curated list of research papers, code repositories, and benchmarks that focus on the intersection of LLMs with planning and reasoning tasks. Here, you'll find:
Techniques: Innovative methods that enable LLMs to reason and plan effectively, such as Chain-of-Thought prompting and Tree of Thoughts.
Reasoning Limitations: Critical investigations that explore the limitations and challenges LLMs face in planning and reasoning tasks.
Benchmarks: Standardized tests and evaluations designed to measure the performance of LLMs in these complex tasks.
Miscellaneous Papers: Papers related to the field of LLMs and reasoning, but not directly focused on planning tasks.
Additional Resources: Supplementary materials such as slides, dissertations, and other resources that provide further insights into LLM planning and reasoning.
Whether you're a researcher, developer, or enthusiast, this repository serves as a comprehensive resource for staying updated on the latest advancements and understanding the current challenges in the domain of LLMs' planning and reasoning abilities. Dive in and explore the fascinating world where language models meet high-level cognitive tasks!
Techniques
Paper
Link
Code
Venue
Date
Other
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
awesome-llm-planning-reasoning
About
Welcome to the Awesome LLMs Planning Reasoning repository! This collection is dedicated to exploring the rapidly evolving field of Large Language Models (LLMs) and their capabilities in planning and reasoning.
Overview
As LLMs continue to demonstrate remarkable success in Natural Language Understanding (NLU) and Natural Language Generation (NLG), researchers are increasingly interested in assessing their abilities beyond traditional NLP tasks. One of the most promising and challenging areas of study is understanding how well LLMs can perform tasks that require planning and reasoning. These capabilities are essential for leveraging LLMs in more complex, real-world scenarios, such as autonomous decision-making, problem-solving, and strategic thinking. However, recent research suggests that LLMs often struggle with reasoning tasks that are relatively simple for most humans, highlighting the limitations of these models in this critical area.
This repository is a curated list of research papers, code repositories, and benchmarks that focus on the intersection of LLMs with planning and reasoning tasks. Here, you'll find:
Whether you're a researcher, developer, or enthusiast, this repository serves as a comprehensive resource for staying updated on the latest advancements and understanding the current challenges in the domain of LLMs' planning and reasoning abilities. Dive in and explore the fascinating world where language models meet high-level cognitive tasks!
Techniques
Reasoning Limitations
Benchmarks
Suggested labels
None