It only uses the learnable prompt vector and not the GNN weights, which are frozen for downstream tasks. This reduces the number of parameters that need to be updated, improves the computational efficiency of task learning/inference, and reduces the reliance on labeled data.
PROMPT ENGINEERING
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Prompt Tuning Optimizes Downstream Task Efficiency and Accuracy
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Prompt tuning involves optimizing the learnable prompt to improve the computational efficiency and accuracy of downstream tasks. It is based on the similarity of subgraphs and is formulated using prompt-assisted task-specific subgraph representations.
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Learnable Prompts Enable Better Task-Specific Knowledge Extraction
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Learnable prompts provide a better alternative to handcrafted prompts, and enable the extraction of the most relevant prior knowledge for each task. The prompts are a dimension-wise reweighting (or a linear transformation) of the node representations.
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GraphPrompt: Unified Pre-Training Framework for Graph Neural Networks
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GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks Interesting pre-training training framework for GNNs, based on learnable prompts. It reduces labeling needs and boosts downstream task performance. https://
arxiv.org/abs/2302.08043 -
GPTs Execute Natural Language Programs Through Document Completion
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9/ Pulling in one more relevant tweet of mine from a while ago. GPTs run natural language programs by completing the document.
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GPT as Backend: LLM-Powered State Management with Natural Language
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6/ "GPT is all you need for the backend" https://
github.com/TheAppleTucker
/backend-GPT
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Tired: use an LLM to help you write a backend
Wired: LLM is the backend
Inspiring project from a recent Scale hackathon. The LLM backend takes state as JSON blob and modifies it based on… English description. -
Bing Chat’s Prompt Revealed by Injection, Identity Construction
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7/ The prompt allegedly used by Bing chat, potentially spilled by a prompt injection attack https://x.com/marvinvonhagen/status/1623658144349011971?lang=en … important point for our purposes is that the identity is constructed and programmed in English, by laying out who it is, what it knows/doesn't know, and how to act.
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Prompt Engineering as LLM Psychology: Why Prompts Matter
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8/ These examples illustrate how prompts 1: matter and 2: are not trivial, and why today it makes sense to be a "prompt engineer" (e.g. @goodside ). I also like to think of this role as a kind of LLM psychologist.
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ChatGPT iOS Shortcut Creates Advanced HomeKit Voice Assistant
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5/ "ChatGPT in an iOS Shortcut — Worlds Smartest HomeKit Voice Assistant" https://
matemarschalko.medium.com/chatgpt-in-an-
ios-shortcut-worlds-smartest-homekit-voice-assistant-9a33b780007a
… This voice assistant is significantly more capable and personalized than your regular Siri/Alexa/etc., and it was programmed in English. -
Prompts Enable Complex Multi-Step Reasoning Through Strategic Design
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2/ These two [1] https://
arxiv.org/abs/2205.11916 , [2] https://
arxiv.org/abs/2211.01910 are good examples that the prompt can further program the "solution strategy", and with a good enough design of it, a lot more complex multi-step reasoning tasks become possible.