commit
ab3f07e281
|
@ -14,6 +14,10 @@
|
|||
"title": "About",
|
||||
"type": "page"
|
||||
},
|
||||
"course":{
|
||||
"title": "Prompt Engineering Course",
|
||||
"type": "page"
|
||||
},
|
||||
"contact": {
|
||||
"title": "Contact ↗",
|
||||
"type": "page",
|
||||
|
|
|
@ -14,6 +14,10 @@
|
|||
"title": "About",
|
||||
"type": "page"
|
||||
},
|
||||
"course":{
|
||||
"title": "Prompt Engineering Course",
|
||||
"type": "page"
|
||||
},
|
||||
"contact": {
|
||||
"title": "Contact ↗",
|
||||
"type": "page",
|
||||
|
@ -21,4 +25,3 @@
|
|||
"newWindow": true
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
# Prompt Engineering Course
|
||||
|
||||
We have partnered with Sphere to deliver a ["Prompting Engineering for LLMs"](https://www.getsphere.com/cohorts/prompt-engineering-for-llms?source=promptingguide) course in May, 2023.
|
||||
|
||||
This hands-on course is designed to teach all the latest prompt engineering techniques and tools used in the real-world for effectively building applications of top of large language models.
|
||||
|
||||
If you want to take your prompt engineering skills to the next level, we highly recommend the course.
|
||||
|
||||
This course also includes a certificate of completion.
|
|
@ -0,0 +1,11 @@
|
|||
# Prompt Engineering Course
|
||||
|
||||
We have partnered with Sphere to deliver a ["Prompting Engineering for LLMs"](https://www.getsphere.com/cohorts/prompt-engineering-for-llms?source=promptingguide) course in May, 2023.
|
||||
|
||||
This hands-on course is designed to teach all the latest prompt engineering techniques and tools used in the real-world for effectively building applications of top of large language models.
|
||||
|
||||
If you want to take your prompt engineering skills to the next level, we highly recommend the course.
|
||||
|
||||
This course also includes a certificate of completion.
|
||||
|
||||
Note that this course will be delivered in English.
|
|
@ -145,6 +145,23 @@ The current recommendation for `gpt-3.5-turbo-0301` is to add instructions in th
|
|||
---
|
||||
## References
|
||||
|
||||
- [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in HuggingFace](https://arxiv.org/abs/2303.17580) (March 2023)
|
||||
- [WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research](https://arxiv.org/abs/2303.17395) (March 2023)
|
||||
- [Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://arxiv.org/abs/2303.17466) (March 2023)
|
||||
- [Yes but.. Can ChatGPT Identify Entities in Historical Documents?](https://arxiv.org/abs/2303.17322) (March 2023)
|
||||
- [Evaluation of ChatGPT for NLP-based Mental Health Applications](https://arxiv.org/abs/2303.15727) (March 2023)
|
||||
- [A Perspectival Mirror of the Elephant: Investigating Language Bias on Google, ChatGPT, Wikipedia, and YouTube](https://arxiv.org/abs/2303.16281) (March 2023)
|
||||
- [ChatGPT or academic scientist? Distinguishing authorship with over 99% accuracy using off-the-shelf machine learning tools](https://arxiv.org/abs/2303.16352) (March 2023)
|
||||
- [Zero-shot Clinical Entity Recognition using ChatGPT](https://arxiv.org/abs/2303.16416) (March 2023)
|
||||
- [ChatGPT is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language Models](https://arxiv.org/abs/2303.16421) (March 2023)
|
||||
- [ChatGPT4PCG Competition: Character-like Level Generation for Science Birds](https://arxiv.org/abs/2303.15662) (March 2023)
|
||||
- [ChatGPT as a Factual Inconsistency Evaluator for Abstractive Text Summarization](https://arxiv.org/abs/2303.15621) (March 2023)
|
||||
- [Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System](https://arxiv.org/abs/2303.14524) (March 2023)
|
||||
- [A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability](https://arxiv.org/abs/2303.13547) (March 2023)
|
||||
- [Towards Making the Most of ChatGPT for Machine Translation](https://arxiv.org/abs/2303.13780) (March 2023)
|
||||
- [Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models: A Case Study on ChatGPT](https://arxiv.org/abs/2303.13809) (March 2023)
|
||||
- [ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks](https://arxiv.org/pdf/2303.15056v1.pdf) (March 2023)
|
||||
- [ChatGPT or Grammarly? Evaluating ChatGPT on Grammatical Error Correction Benchmark](https://arxiv.org/abs/2303.13648) (March 2023)
|
||||
- [ChatGPT and a New Academic Reality: AI-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishing](https://arxiv.org/abs/2303.13367) (March 2023)
|
||||
- [Are LLMs the Master of All Trades? : Exploring Domain-Agnostic Reasoning Skills of LLMs](https://arxiv.org/abs/2303.12810) (March 2023)
|
||||
- [Is ChatGPT A Good Keyphrase Generator? A Preliminary Study](https://arxiv.org/abs/2303.13001) (March 2023)
|
||||
|
|
|
@ -160,6 +160,10 @@ Coming soon!
|
|||
|
||||
## References
|
||||
|
||||
- [Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams](https://arxiv.org/abs/2303.17003) (March 2023)
|
||||
- [GPTEval: NLG Evaluation using GPT-4 with Better Human Alignment](https://arxiv.org/abs/2303.16634) (March 2023)
|
||||
- [Humans in Humans Out: On GPT Converging Toward Common Sense in both Success and Failure](https://arxiv.org/abs/2303.17276) (March 2023)
|
||||
- [GPT is becoming a Turing machine: Here are some ways to program it](https://arxiv.org/abs/2303.14310) (March 2023)
|
||||
- [Mind meets machine: Unravelling GPT-4's cognitive psychology](https://arxiv.org/abs/2303.11436) (March 2023)
|
||||
- [Capabilities of GPT-4 on Medical Challenge Problems](https://www.microsoft.com/en-us/research/uploads/prod/2023/03/GPT-4_medical_benchmarks.pdf) (March 2023)
|
||||
- [GPT-4 Technical Report](https://cdn.openai.com/papers/gpt-4.pdf) (March 2023)
|
||||
|
|
|
@ -34,6 +34,7 @@ Overall, LLaMA-13B outperform GPT-3(175B) on many benchmarks despite being 10x s
|
|||
|
||||
## References
|
||||
|
||||
- [LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention](https://arxiv.org/abs/2303.16199) (March 2023)
|
||||
- [GPT4All](https://github.com/nomic-ai/gpt4all) (March 2023)
|
||||
- [ChatDoctor: A Medical Chat Model Fine-tuned on LLaMA Model using Medical Domain Knowledge](https://arxiv.org/abs/2303.14070) (March 2023)
|
||||
- [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) (March 2023)
|
|
@ -4,6 +4,7 @@ The following are the latest papers (sorted by release date) on prompt engineeri
|
|||
|
||||
## Overviews
|
||||
|
||||
- [Nature Language Reasoning, A Survey](https://arxiv.org/abs/2303.14725) (March 2023)
|
||||
- [Augmented Language Models: a Survey](https://arxiv.org/abs/2302.07842) (Feb 2023)
|
||||
- [A Survey for In-context Learning](https://arxiv.org/abs/2301.00234) (Dec 2022)
|
||||
- [Towards Reasoning in Large Language Models: A Survey](https://arxiv.org/abs/2212.10403) (Dec 2022)
|
||||
|
@ -14,8 +15,9 @@ The following are the latest papers (sorted by release date) on prompt engineeri
|
|||
|
||||
## Approaches
|
||||
|
||||
- [Visual-Language Prompt Tuning with Knowledge-guided Context Optimization](https://arxiv.org/abs/2303.13283) (March 2023)
|
||||
- [Fairness-guided Few-shot Prompting for Large Language Models](https://arxiv.org/abs/2303.13217) (March 2023)
|
||||
- [kNN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference](https://arxiv.org/abs/2303.13824) (Mar 2023)
|
||||
- [Visual-Language Prompt Tuning with Knowledge-guided Context Optimization](https://arxiv.org/abs/2303.13283) (Mar 2023)
|
||||
- [Fairness-guided Few-shot Prompting for Large Language Models](https://arxiv.org/abs/2303.13217) (Mar 2023)
|
||||
- [Context-faithful Prompting for Large Language Models](https://arxiv.org/abs/2303.11315) (Mar 2023)
|
||||
- [Is Prompt All You Need? No. A Comprehensive and Broader View of Instruction Learning](https://arxiv.org/abs/2303.10475) (Mar 2023)
|
||||
- [UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation](https://arxiv.org/abs/2303.08518) (Mar 2023)
|
||||
|
@ -116,6 +118,16 @@ The following are the latest papers (sorted by release date) on prompt engineeri
|
|||
|
||||
## Applications
|
||||
|
||||
- [BloombergGPT: A Large Language Model for Finance](https://arxiv.org/abs/2303.17564) (March 2023)
|
||||
- [Medical Intervention Duration Estimation Using Language-enhanced Transformer Encoder with Medical Prompts](https://arxiv.org/abs/2303.17408) (March 2023)
|
||||
- [Soft-prompt tuning to predict lung cancer using primary care free-text Dutch medical notes](https://arxiv.org/abs/2303.15846) (March 2023)
|
||||
- [TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs](https://arxiv.org/abs/2303.16434) (March 2023)
|
||||
- [Larger Probes Tell a Different Story: Extending Psycholinguistic Datasets Via In-Context Learning](https://arxiv.org/abs/2303.16445) (March 2023)
|
||||
- [Linguistically Informed ChatGPT Prompts to Enhance Japanese-Chinese Machine Translation: A Case Study on Attributive Clauses](https://arxiv.org/abs/2303.15587) (March 2023)
|
||||
- [Knowledge-augmented Frame Semantic Parsing with Hybrid Prompt-tuning](https://arxiv.org/abs/2303.14375) (March 2023)
|
||||
- [Debiasing Scores and Prompts of 2D Diffusion for Robust Text-to-3D Generation](https://arxiv.org/abs/2303.15413) (March 2023)
|
||||
- [Zero-shot Model Diagnosis](https://arxiv.org/abs/2303.15441#) (March 2023)
|
||||
- [Prompting Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages](https://arxiv.org/abs/2303.13592) (March 2023)
|
||||
- [SPeC: A Soft Prompt-Based Calibration on Mitigating Performance Variability in Clinical Notes Summarization](https://arxiv.org/abs/2303.13035) (March 2023)
|
||||
- [Large Language Models and Simple, Stupid Bugs](https://arxiv.org/abs/2303.11455) (March 2023)
|
||||
- [Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses?](https://arxiv.org/abs/2303.09325) (Mar 2023)
|
||||
|
@ -151,6 +163,7 @@ The following are the latest papers (sorted by release date) on prompt engineeri
|
|||
- [Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language](https://arxiv.org/abs/2210.15157) (Oct 2022)
|
||||
- [Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?](https://arxiv.org/abs/2210.14699) (Oct 2022)
|
||||
- [Plot Writing From Scratch Pre-Trained Language Models](https://aclanthology.org/2022.inlg-main.5) (July 2022)
|
||||
- [Survey of Hallucination in Natural Language Generation](https://arxiv.org/abs/2202.03629) (Feb 2022)
|
||||
|
||||
## Collections
|
||||
|
||||
|
|
|
@ -6,7 +6,6 @@
|
|||
- [A beginner-friendly guide to generative language models - LaMBDA guide](https://aitestkitchen.withgoogle.com/how-lamda-works)
|
||||
- [A Complete Introduction to Prompt Engineering for Large Language Models](https://www.mihaileric.com/posts/a-complete-introduction-to-prompt-engineering)
|
||||
- [A Generic Framework for ChatGPT Prompt Engineering](https://medium.com/@thorbjoern.heise/a-generic-framework-for-chatgpt-prompt-engineering-7097f6513a0b)
|
||||
- [CS 324 - Advances in Foundation Models](https://stanford-cs324.github.io/winter2023/)
|
||||
- [An SEO’s guide to ChatGPT prompts](https://searchengineland.com/chatgpt-prompts-seo-393523)
|
||||
- [AI Content Generation](https://www.jonstokes.com/p/ai-content-generation-part-1-machine)
|
||||
- [AI's rise generates new job title: Prompt engineer](https://www.axios.com/2023/02/22/chatgpt-prompt-engineers-ai-job)
|
||||
|
@ -19,11 +18,13 @@
|
|||
- [Can AI really be protected from text-based attacks?](https://techcrunch.com/2023/02/24/can-language-models-really-be-protected-from-text-based-attacks/)
|
||||
- [ChatGPT, AI and GPT-3 Apps and use cases](https://gpt3demo.com)
|
||||
- [ChatGPT Prompts](https://twitter.com/aaditsh/status/1636398208648658945?s=20)
|
||||
- [ChatGPT Plugins Collection ⭐️ (unofficial)](https://github.com/logankilpatrick/ChatGPT-Plugins-Collection)
|
||||
- [CMU Advanced NLP 2022: Prompting](https://youtube.com/watch?v=5ef83Wljm-M&feature=shares)
|
||||
- [Common Sense as Dark Matter - Yejin Choi | Stanford MLSys #78](https://youtube.com/live/n4HakBqoCVg?feature=shares)
|
||||
- [Create images with your words – Bing Image Creator comes to the new Bing](https://blogs.microsoft.com/blog/2023/03/21/create-images-with-your-words-bing-image-creator-comes-to-the-new-bing/)
|
||||
- [Curtis64's set of prompt gists](https://gist.github.com/Curtis-64)
|
||||
- [CS324 - Large Language Models](https://stanford-cs324.github.io/winter2022/)
|
||||
- [CS 324 - Advances in Foundation Models](https://stanford-cs324.github.io/winter2023/)
|
||||
- [CS224N: Natural Language Processing with Deep Learning](https://web.stanford.edu/class/cs224n/)
|
||||
- [DALL·E 2 Prompt Engineering Guide](https://docs.google.com/document/d/11WlzjBT0xRpQhP9tFMtxzd0q6ANIdHPUBkMV-YB043U/edit#)
|
||||
- [DALL·E 2 Preview - Risks and Limitations](https://github.com/openai/dalle-2-preview/blob/main/system-card.md)
|
||||
|
@ -61,6 +62,7 @@
|
|||
- [NLP for Text-to-Image Generators: Prompt Analysis](https://heartbeat.comet.ml/nlp-for-text-to-image-generators-prompt-analysis-part-1-5076a44d8365)
|
||||
- [NLP with Deep Learning CS224N/Ling284 - Lecture 11: Promting, Instruction Tuning, and RLHF](http://web.stanford.edu/class/cs224n/slides/cs224n-2023-lecture11-prompting-rlhf.pdf)
|
||||
- [Notes for Prompt Engineering by sw-yx](https://github.com/sw-yx/ai-notes)
|
||||
- [On pitfalls (and advantages) of sophisticated large language models](https://arxiv.org/abs/2303.17511)
|
||||
- [OpenAI Cookbook](https://github.com/openai/openai-cookbook)
|
||||
- [OpenAI Prompt Examples for several applications](https://platform.openai.com/examples)
|
||||
- [Pretrain, Prompt, Predict - A New Paradigm for NLP](http://pretrain.nlpedia.ai)
|
||||
|
|
Loading…
Reference in New Issue