文章链接:REPLUG: Retrieval-Augmented Black-Box Language Models 一、研究问题 之前检索增强的方法需要访问lm的内部表示(需要训练lm等),很难应用到比较大的lm中,计算量会非常大,或是仅仅提供api的lm不能访问内部。 本文提出了一个新的检索增强的框架RePlug(Retrieve and Plug),把检索组件作为即插即用的插件,其中l...
We introduce REPLUG, a retrieval-augmented language modeling framework that treats the language model (LM) as a black box and augments it with a tuneable retrieval model. Unlike prior retrieval-augmented LMs that train language models with special cross attention mechanisms to encode the retrieved ...
Replug: Retrieval-augmented black-box language models. arXiv preprint arXiv:2301.12652, 2023. [Srivastava等人,2022] Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adri`a Garriga-Alonso, et al. Beyond...
REPLUG: Retrieval-Augmented Black-Box Language Models Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, M. Lewis, Luke Zettlemoyer, Wen-tau Yih 2023 Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering ...
Large Language Models (LLMs) play powerful, black-box readers in the retrieve-then-read pipeline, making remarkable progress in knowledge-intensive tasks. This work introduces a new framework, Rewrite-Retrieve-Read instead of the previous retrieve-then-read for the retrieval-augmented LLMs from the...
Retrieve Anything To Augment Large Language Models Replug: Retrieval-augmented black-box language models When Language Model Meets Private Library EditSum: {A} Retrieve-and-Edit Framework for Source Code Summarization Synchromesh: Reliable Code Generation from Pre-trained Language Models ...
REPLUG: Retrieval-Augmented Black-Box Language Models Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih arXiv – Jan 2023 [paper] Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks Patrick Lewis, Ethan Perez, Aleksandra P...
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The RaCNN was found to be especially robust to the black-box, decision-based attack. The proposed approach consists of three major com- ponents; (1) local characterization of data manifold, (2) data manifold projection and (3) regularized learning on the 1...
“Retrieval-Augmented Generation for Large Language Models: A Survey”理解 1、对新模式中对DSP(DEMONSTRATE–SEARCH–PREDICT)的理解: 1.1、对新模式中DSP的理解: 上图展示了一个名为DSP(Demonstrate-Search-Predict,即展示-搜索-预测)程序用于多跳问答