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A Survey on Retrieval-Augmented Text Generation

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arxiv 2202.01110 v2 pith:2XESC6B7 submitted 2022-02-02 cs.CL

Huayang Li , Yixuan Su , Deng Cai , Yan Wang , Lemao Liu This is my paper · ORCID
classification cs.CL
keywords generationretrieval-augmentedtexttaskssurveyaccordingachievedadvantages
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Recently, retrieval-augmented text generation attracted increasing attention of the computational linguistics community. Compared with conventional generation models, retrieval-augmented text generation has remarkable advantages and particularly has achieved state-of-the-art performance in many NLP tasks. This paper aims to conduct a survey about retrieval-augmented text generation. It firstly highlights the generic paradigm of retrieval-augmented generation, and then it reviews notable approaches according to different tasks including dialogue response generation, machine translation, and other generation tasks. Finally, it points out some important directions on top of recent methods to facilitate future research.

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Cited by 28 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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  4. DARTH: Declarative Recall Through Early Termination for Approximate Nearest Neighbor Search

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    DARTH learns to predict a query's current recall during HNSW/IVF search and stops early at a user-specified target, achieving speedups up to 14.6x on HNSW and 41.8x on IVF, yet 13-15% of queries miss the target.

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  17. SCRAG: Social Computing-Based Retrieval Augmented Generation for Community Response Forecasting in Social Media Environments

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  19. Network-informed Prompt Engineering against Organized Astroturf Campaigns under Extreme Class Imbalance

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    Frozen LLMs with balanced retrieval-augmented prompting detect astroturf campaigns better than GNN baselines on a 2016 US election dataset, but the reported margins are overstated.

  20. Multi-modal Retrieval Augmented Multi-modal Generation: Datasets, Evaluation Metrics and Strong Baselines

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  21. Position: The ML Community Must Build an AI-Augmented Peer-Review Ecosystem

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    In a single-document pilot, a four-agent LLM translation workflow scored higher on adequacy and fluency than DeepL or Google Translate for English-Spanish legal text, but the result lacks statistical support and a sin...

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  24. Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey

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