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T06. RAG, knowledge graphs, ontologies, and provenance

Retrieval-augmented generation and structured knowledge with traceable sources.

  1. T06-14Similar problemSince 2025

    Enhancing retrieval-augmented generation for interoperable industrial knowledge representation and inference toward cognitive digital twins

    Authors
    Dachuan Shi, Jianzhang Li, Olga Meyer, Thomas Bauernhansl
    Year
    2025
    Venue
    Computers in Industry vol. 171, 2025, 104330

    Korean review of T06-14

  2. T06-1Structural parallel

    Dense Passage Retrieval for Open-Domain Question Answering

    Authors
    Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih
    Year
    2020
    Venue
    EMNLP 2020, pp. 6769-6781

    Korean review of T06-1

  3. T06-2Similar problem

    Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

    Authors
    Patrick Lewis and 11 others
    Year
    2020
    Venue
    NeurIPS 2020

    Korean review of T06-2

  4. T06-3Structural parallel

    Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

    Authors
    Gautier Izacard, Edouard Grave
    Year
    2021
    Venue
    EACL 2021, pp. 874-880

    Korean review of T06-3

  5. T06-4Similar problem

    Retrieval-Augmented Generation for Large Language Models: A Survey

    Authors
    Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Meng Wang, Haofen Wang
    Year
    2024
    Venue
    arXiv (v1 2023-12-18, v5 2024-03-27)

    Korean review of T06-4

  6. T06-5Structural parallel

    From Local to Global: A Graph RAG Approach to Query-Focused Summarization

    Authors
    Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, Dasha Metropolitansky, Robert Osazuwa Ness, Jonathan Larson
    Year
    2025
    Venue
    arXiv, Microsoft Research (v1 2024-04-24, v2 2025-02-19)

    Korean review of T06-5

  7. T06-6Candidate approach

    HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models

    Authors
    Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, Michihiro Yasunaga, Yu Su
    Year
    2024
    Venue
    NeurIPS 2024

    Korean review of T06-6

  8. T06-7Structural parallel

    Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

    Authors
    Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, Hannaneh Hajishirzi
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T06-7

  9. T06-8Structural parallel

    Enabling Large Language Models to Generate Text with Citations

    Authors
    Tianyu Gao, Howard Yen, Jiatong Yu, Danqi Chen
    Year
    2023
    Venue
    EMNLP 2023, pp. 6465-6488

    Korean review of T06-8

  10. T06-9Similar problem

    Measuring Attribution in Natural Language Generation Models

    Authors
    Hannah Rashkin, Vitaly Nikolaev, Matthew Lamm, Lora Aroyo, Michael Collins, Dipanjan Das, Slav Petrov, Gaurav Singh Tomar, Iulia Turc, David Reitter
    Year
    2023
    Venue
    Computational Linguistics vol. 49 no. 4, 2023, pp. 777-840

    Korean review of T06-9

  11. T06-10Structural parallel

    Provenance Semirings

    Authors
    Todd J. Green, Grigoris Karvounarakis, Val Tannen
    Year
    2007
    Venue
    PODS 2007 (ACM SIGMOD-SIGACT-SIGART Principles of Database Systems), pp. 31-40

    Korean review of T06-10

  12. T06-11Structural parallel

    Provenance in Databases: Why, How, and Where

    Authors
    James Cheney, Laura Chiticariu, Wang-Chiew Tan
    Year
    2009
    Venue
    Foundations and Trends in Databases vol. 1 no. 4, 2009, pp. 379-474

    Korean review of T06-11

  13. T06-12Similar problem

    Knowledge Graphs

    Authors
    Aidan Hogan and 17 others
    Year
    2022
    Venue
    ACM Computing Surveys vol. 54 no. 4, 71, pp. 1-37

    Korean review of T06-12

  14. T06-13Similar problem

    A benchmark dataset with Knowledge Graph generation for Industry 4.0 production lines

    Authors
    Muhammad Yahya, Aabid Ali, Qaiser Mehmood, Lan Yang, John G. Breslin, Muhammad Intizar Ali
    Year
    2024
    Venue
    Semantic Web vol. 15 no. 2, 2024, pp. 461-479

    Korean review of T06-13

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