Prompt4ReasoningPapers
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How to install Prompt4ReasoningPapers?
zjunlp/prompt4reasoningpapers
$git clone https://github.com/zjunlp/Prompt4ReasoningPapers---
README.md
| 1 | # Reasoning with Language Model Prompting Papers |
| 2 | [](https://github.com/zjunlp/Prompt4ReasoningPapers) |
| 3 | [](https://opensource.org/licenses/MIT) |
| 4 |  |
| 5 |  |
| 6 | |
| 7 | ## 🔔 News |
| 8 | - **2024-03-05 We release a new paper: "[KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents](https://arxiv.org/abs/2403.03101)".** |
| 9 | - **2024-02-06 We release a new paper: "[EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models](https://arxiv.org/abs/2402.03049)" with an HF demo [EasyInstruct](https://huggingface.co/spaces/zjunlp/EasyInstruct).** |
| 10 | - **2024-01-03 We release a new paper:"[A Comprehensive Study of Knowledge Editing for Large Language Models](https://arxiv.org/abs/2401.01286)" with a new benchmark [KnowEdit](https://huggingface.co/datasets/zjunlp/KnowEdit)! We are looking forward to any comments or discussions on this topic :)** |
| 11 | - **2023-7-12 We release [EasyEdit](https://github.com/zjunlp/EasyEdit), an easy-to-use knowledge editing framework for Large Language Models.** |
| 12 | - **2023-6-19 We open-source [KnowLM](https://github.com/zjunlp/KnowLM), a knowledgeable large language model framework with pre-training and instruction fine-tuning code (supports multi-machine multi-GPU setup) and various LLMs**. |
| 13 | - **2023-3-27 We release [EasyInstruct](https://github.com/zjunlp/EasyInstruct), a package for instructing Large Language Models (LLMs) like ChatGPT in your research experiments. It is designed to be easy to use and easy to extend!** |
| 14 | - **2023-2-19 We upload a [tutorial](https://github.com/zjunlp/Prompt4ReasoningPapers/blob/main/tutorial.pdf) of our survey paper to help you learn more about reasoning with language model prompting (Attached with a [video](https://www.techbeat.net/talk-info?id=756) (Chinese) of the tutorial).** |
| 15 | - **2022-12-19 We release a new survey paper:"[Reasoning with Language Model Prompting: A Survey](https://arxiv.org/abs/2212.09597)" based on this repository! We are looking forward to any comments or discussions on this topic :)** |
| 16 | - **2022-09-14 We create this repository to maintain a paper list on *Reasoning with Language Model Prompting*.** |
| 17 | |
| 18 | --- |
| 19 | |
| 20 | ## 🔍 Contents |
| 21 | |
| 22 | - [🌟 Introduction](#-introduction) |
| 23 | - [📜 Papers](#-papers) |
| 24 | - [Overview](#overview) |
| 25 | - [Methods](#methods) |
| 26 | - [Strategy Enhanced Reasoning](#strategy-enhanced-reasoning) |
| 27 | - [Prompt Engineering](#prompt-engineering) |
| 28 | - [Single-Stage](#single-stage) |
| 29 | - [Multi-Stage](#multi-stage) |
| 30 | - [Process Optimization](#process-Optimization) |
| 31 | - [Self-Optimization](#self-optimization) |
| 32 | - [Ensemble-Optimization](#ensemble-optimization) |
| 33 | - [Iterative-Optimization](#iterative-optimization) |
| 34 | - [External Engine](#external-engine) |
| 35 | - [Physical Simulator](#physical-simulator) |
| 36 | - [Code Interpreter](#code-interpreter) |
| 37 | - [Tool Learning](#tool-learning) |
| 38 | - [Knowledge Enhanced Reasoning](#knowledge-enhanced-reasoning) |
| 39 | - [Implicit Knowledge](#implicit-knowledge) |
| 40 | - [Explicit Knowledge](#explicit-knowledge) |
| 41 | - [Others](#others) |
| 42 | - [Analysis](#analysis) |
| 43 | - [🧰 Resources](#-resources) |
| 44 | - [Benchmarks and Tasks](#benchmarks-and-tasks) |
| 45 | - [Tools](#tools) |
| 46 | - [🎉 Contributing](#-contributing) |
| 47 | - [🚩Citation ](#-citation) |
| 48 | |
| 49 | --- |
| 50 | |
| 51 | ## 🌟 Introduction |
| 52 | |
| 53 | Reasoning, as an essential ability for complex problem-solving, can provide back-end support for various real-world applications, such as medical diagnosis, negotiation, etc. This paper provides a comprehensive survey of cutting-edge research on reasoning with language model prompting. We introduce research works with comparisons and summaries and provide systematic resources to help beginners. We also discuss the potential reasons for emerging such reasoning abilities and highlight future research |
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