Solving Reasoning Problems with LLMs in 2023

It's the beginning of 2024 and ChatGPT just celebrated its one-year birthday. One year is a super long time for the community of large language models, where a myriad of interesting works have taken place. Let's revisit the progress and discuss topics for the coming year.

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_This post was co-authored with Michael Galkin (Intel AI Lab), Abulhair Saparov (New York University), Shibo Hao (UC San Diego) and Yihong Chen (University College London & Meta AI Research). Many insights in this post were formed during the fruitful discussions with Emily Xue (Google), Hanjun Dai (Google DeepMind) and Bruno Ribeiro (Purdue University)._

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Table of Contents

1. Introduction
2. Tool Use
3. In-context learning enables using more tools
4. Most used tools: code interpreters and retrievers
5. Let LLMs create their own tools
6. Reasoning
7. Planning
8. Self series
9. Evaluations and observations
10. What needs to be solved in 2024?

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Introduction

Tags: Agents Artificial Intelligence Editors Pick Large Language Models Reasoning

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