DecryptPrompt
Summarizes Prompt&LLM Papers, Open-source Data&Models, AIGC Applications
GraphCanon updated 3w · GitHub synced 3w
Decision brief
DecryptPrompt is an open-source repository that summarizes prompt and large language model research papers while offering related datasets and models for AI content generation facilitation.
Good fit when
- When you need detailed summaries of prompt-engineering and LLM-related research, as DecryptPrompt is dedicated to this area.
- If your project requires access to open-source data sets and models specifically connected with prompt research, given that DecryptPrompt focuses on providing these resources.
Avoid when
- Avoid using DecryptPrompt if you require a solution that supports languages other than English effectively, as the repository's descriptions are in Chinese.
- If your development needs go beyond summarization and data/model provision into complex coding examples or comprehensive API documentation, DecryptPrompt might not satisfy these requirements.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Steady (83d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/DSXiangLi/DecryptPromptSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
DecryptPrompt is an open-source repository summarizing prompt and LLM research papers along with providing associated data sets and models to facilitate understanding and development in AI-driven content generation.
Capability facts
No sourced capability facts yet. Facts appear after ingest scans repo manifests (Dockerfile, package.json, MCP configs).
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README
DecryptPrompt
如果LLM的突然到来让你感到沮丧，不妨读下主目录的Choose Your Weapon Survival Strategies for Depressed AI Academics 持续更新以下内容，Star to keep updated~
LLM资源汇总
- 开源模型和评测榜单
- 开源推理，微调，Agent，RAG，propmt 框架
- 开源SFT，RLHF，Pretrain 数据集
- AIGC各领域应用汇总
- Prompt教程，经典博客和AI会议访谈
跟着博客读论文
- 解密Prompt系列1. Tunning-Free Prompt：GPT2 & GPT3 & LAMA & AutoPrompt
- 解密Prompt系列2. 冻结Prompt微调LM： T5 & PET & LM-BFF
- 解密Prompt系列3. 冻结LM微调Prompt: Prefix-tuning & Prompt-tuning & P-tuning
- 解密Prompt系列4. 升级Instruction Tuning：Flan/T0/InstructGPT/TKInstruct
- 解密prompt系列5. APE+SELF=自动化指令集构建代码实现
- 解密Prompt系列6. lora指令微调扣细节-请冷静,1个小时真不够~
- 解密Prompt系列7. 偏好对齐RLHF-OpenAI·DeepMind·Anthropic对比分析
- 解密Prompt系列8. 无需训练让LLM支持超长输入:知识库 & Unlimiformer & PCW & NBCE
- 解密Prompt系列9. COT：模型复杂推理-思维链基础和进阶玩法
- 解密Prompt系列10. COT：思维链COT原理探究
- 解密Prompt系列11. COT：小模型也能COT，先天不足后天补
- 解密Prompt系列12. LLM Agent零微调范式 ReAct & Self Ask
- 解密Prompt系列13. LLM Agent指令微调方案: Toolformer & Gorilla
- 解密Prompt系列14. LLM Agent之搜索应用设计：WebGPT & WebGLM & WebCPM
- 解密Prompt系列15. LLM Agent之数据库应用设计：DIN & C3 & SQL-Palm & BIRD
- 解密Prompt系列16. LLM对齐经验之数据越少越好？LTD & LIMA & AlpaGasus
- 解密Prompt系列17. LLM对齐方案再升级 WizardLM & BackTranslation & SELF-ALIGN
- 解密Prompt系列18. LLM Agent之只有智能体的世界
- 解密Prompt系列19. LLM Agent之数据分析领域的应用：Data-Copilot & InsightPilot
- 解密Prompt系列20. RAG之再谈召回多样性优化
- 解密Prompt系列21. RAG之再谈召回信息密度和质量
- 解密Prompt系列22. RAG的反思：放弃了压缩还是智能么？
- 解密Prompt系列23.大模型幻觉分类&归因&检测&缓解方案脑图全梳理
- 解密prompt系列24. RLHF新方案之训练策略：SLiC-HF & DPO & RRHF & RSO
- 解密prompt系列25. RLHF改良方案之样本标注：RLAIF & SALMON
- 解密prompt系列26. 人类思考vs模型思考：抽象和发散思维
- 解密prompt系列27. LLM对齐经验之如何降低通用能力损失
- 解密Prompt系列28. LLM Agent之金融领域智能体：FinMem & FinAgent
- 解密Prompt系列29. LLM Agent之真实世界海量API解决方案：ToolLLM & AnyTool
- 解密Prompt系列30. LLM Agent之互联网冲浪智能体们
- 解密Prompt系列31. LLM Agent之从经验中不断学习的智能体
- 解密Prompt系列32. LLM之表格理解任务-文本模态
- 解密Prompt系列33. LLM之图表理解任务-多模态篇
- 解密prompt系列34. RLHF之训练另辟蹊径：循序渐进 & 青出于蓝
- [解密prompt系列35. Prom
For agents
This page has a .md twin and JSON over the API.