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Overview of Touché 2022: Argument Retrieval

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Advances in Information Retrieval (ECIR 2022)

Abstract

The goal of the Touché lab on argument retrieval is to foster and support the development of technologies for argument mining and argument analysis. In the third edition of Touché, we organize three shared tasks: (a) argument retrieval for controversial topics, where participants retrieve a gist of arguments from a collection of online debates, (b) argument retrieval for comparative questions, where participants retrieve argumentative passages from a generic web crawl, and (c) image retrieval for arguments, where participants retrieve images from a focused web crawl that show support or opposition to some stance. In this paper, we briefly summarize the results of two years of organizing Touché and describe the planned setup for the third edition at CLEF 2022.

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Notes

  1. 1.

    ‘touché’ is commonly “used to acknowledge a hit in fencing or the success or appropriateness of an argument” [https://merriam-webster.com/dictionary/touche].

  2. 2.

    https://trec.nist.gov/tracks.html

  3. 3.

    Also available as a Python library: https://pypi.org/project/targer-api/

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Acknowledgments

This work was partially supported by the Deutsche Forschungsgemeinschaft (DFG) through the projects “ACQuA” and “ACQuA 2.0” (Answering Comparative Questions with Arguments; grants HA 5851/2-1, HA 5851/2-2, BI 1544/7-1, BI 1544/7-2) and “OASiS: Objective Argument Summarization in Search” (grant WA 4591/3-1), all part of the priority program “RATIO: Robust Argumentation Machines” (SPP 1999), and the German Ministry for Science and Education (BMBF) through the project “Shared Tasks as an Innovative Approach to Implement AI and Big Data-based Applications within Universities (SharKI)” (grant FKZ 16DHB4021). We are also grateful to Jan Heinrich Reimer for developing the TARGER Python library.

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Bondarenko, A. et al. (2022). Overview of Touché 2022: Argument Retrieval. In: Hagen, M., et al. Advances in Information Retrieval. ECIR 2022. Lecture Notes in Computer Science, vol 13186. Springer, Cham. https://doi.org/10.1007/978-3-030-99739-7_43

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  • DOI: https://doi.org/10.1007/978-3-030-99739-7_43

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