Logical Scribbles
[공부] 공부 목록 Update 본문
최근 컴퓨터비전에서 자연어처리의 아이디어를 응용하는 사례가 굉장히 많은 것 같다.
Learning How to Ask: Querying LMs with Mixtures of Soft Prompts
Natural-language prompts have recently been used to coax pretrained language models into performing other AI tasks, using a fill-in-the-blank paradigm (Petroni et al., 2019) or a few-shot extrapolation paradigm (Brown et al., 2020). For example, language m
arxiv.org
Prefix-Tuning: Optimizing Continuous Prompts for Generation
Fine-tuning is the de facto way to leverage large pretrained language models to perform downstream tasks. However, it modifies all the language model parameters and therefore necessitates storing a full copy for each task. In this paper, we propose prefix-
arxiv.org
MULTITASK PROMPT TUNING ENABLES PARAMETER-EFFICIENT TRANSFER LEARNING
The Power of Scale for Parameter-Efficient Prompt Tuning
In this work, we explore "prompt tuning", a simple yet effective mechanism for learning "soft prompts" to condition frozen language models to perform specific downstream tasks. Unlike the discrete text prompts used by GPT-3, soft prompts are learned throug
arxiv.org