SIGIR 2023 Workshop on Retrieval Enhanced Machine Learning (REML @ SIGIR 2023)

Michael Bendersky, Fernando Diaz, Danqi Chen, Hamed Zamani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Most machine learning models are designed to be self-contained and encode both “knowledge” and “reasoning” in their parameters. However, such models cannot perform effectively for tasks that require knowledge grounding and tasks that deal with non-stationary data, such as news and social media. Besides, these models often require huge number of parameters to encode all the required knowledge. These issues can be addressed via augmentation with a retrieval model. This category of machine learning models, which is called Retrieval-enhanced machine learning (REML), has recently attracted considerable attention in multiple research communities. For instance, REML models have been studied in the context of open-domain question answering, fact verification, and dialogue systems and also in the context of generalization through memorization in language models and memory networks. We believe that the information retrieval community can significantly contribute to this growing research area by designing, implementing, analyzing, and evaluating various aspects of retrieval models with applications to REML tasks. The goal of this full-day hybrid workshop is to bring together researchers from industry and academia to discuss various aspects of retrieval-enhanced machine learning, including effectiveness, efficiency, and robustness of these models in addition to their impact on real-world applications.

Original languageEnglish (US)
Title of host publicationSIGIR 2023 - Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages3468-3471
Number of pages4
ISBN (Electronic)9781450394086
DOIs
StatePublished - Jul 19 2023
Event46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023 - Taipei, Taiwan, Province of China
Duration: Jul 23 2023Jul 27 2023

Publication series

NameSIGIR 2023 - Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval

Conference

Conference46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023
Country/TerritoryTaiwan, Province of China
CityTaipei
Period7/23/237/27/23

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Information Systems
  • Software

Keywords

  • Knowledge Grounding
  • Memory-Augmented Networks
  • Retrieval Augmentation

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