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75 lines
2.8 KiB
Markdown
75 lines
2.8 KiB
Markdown
# Glossary
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This is a collection of terminology commonly used when developing LLM applications.
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It contains reference to external papers or sources where the concept was first introduced,
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as well as to places in LangChain where the concept is used.
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### Chain of Thought Prompting
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A prompting technique used to encourage the model to generate a series of intermediate reasoning steps.
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A less formal way to induce this behavior is to include “Let’s think step-by-step” in the prompt.
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Resources:
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- [Chain-of-Thought Paper](https://arxiv.org/pdf/2201.11903.pdf)
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- [Step-by-Step Paper](https://arxiv.org/abs/2112.00114)
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### Action Plan Generation
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A prompt usage that uses a language model to generate actions to take.
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The results of these actions can then be fed back into the language model to generate a subsequent action.
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Resources:
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- [WebGPT Paper](https://arxiv.org/pdf/2112.09332.pdf)
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- [SayCan Paper](https://say-can.github.io/assets/palm_saycan.pdf)
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### ReAct Prompting
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A prompting technique that combines Chain-of-Thought prompting with action plan generation.
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This induces the to model to think about what action to take, then take it.
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Resources:
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- [Paper](https://arxiv.org/pdf/2210.03629.pdf)
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- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/docs/examples/agents/react.ipynb)
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### Self-ask
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A prompting method that builds on top of chain-of-thought prompting.
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In this method, the model explicitly asks itself follow-up questions, which are then answered by an external search engine.
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Resources:
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- [Paper](https://ofir.io/self-ask.pdf)
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- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/docs/examples/agents/self_ask_with_search.ipynb)
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### Prompt Chaining
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Combining multiple LLM calls together, with the output of one step being the input to the next.
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Resources:
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- [PromptChainer Paper](https://arxiv.org/pdf/2203.06566.pdf)
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- [Language Model Cascades](https://arxiv.org/abs/2207.10342)
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- [ICE Primer Book](https://primer.ought.org/)
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- [Socratic Models](https://socraticmodels.github.io/)
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### Memetic Proxy
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Encouraging the LLM to respond in a certain way framing the discussion in a context that the model knows of and that will result in that type of response. For example, as a conversation between a student and a teacher.
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Resources:
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- [Paper](https://arxiv.org/pdf/2102.07350.pdf)
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### Self Consistency
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A decoding strategy that samples a diverse set of reasoning paths and then selects the most consistent answer.
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Is most effective when combined with Chain-of-thought prompting.
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Resources:
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- [Paper](https://arxiv.org/pdf/2203.11171.pdf)
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### Inception
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Also called “First Person Instruction”.
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Encouraging the model to think a certain way by including the start of the model’s response in the prompt.
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Resources:
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- [Example](https://twitter.com/goodside/status/1583262455207460865?s=20&t=8Hz7XBnK1OF8siQrxxCIGQ)
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