txsun1997/LMaaS-Papers
Awesome papers on Language-Model-as-a-Service (LMaaS)
This is a curated collection of research papers focused on how to effectively use large language models (LLMs) that are only accessible as a service (e.g., via an API). It helps researchers explore techniques for adapting these powerful models to specific tasks without needing access to their internal parameters or gradients. The collection includes papers on methods like designing text prompts, providing in-context examples, and using black-box optimization. It is intended for NLP researchers and machine learning practitioners who work with LLMs offered as a service.
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Use this if you are an NLP researcher or machine learning practitioner trying to adapt powerful, proprietary large language models (LLMs) to new tasks without access to their underlying code or training data.
Not ideal if you are looking for open-source LLM code to fine-tune directly, or if you are focused on prompt-based learning methods that require model parameter and gradient access.
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May 14, 2024
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