@inproceedings{sviridova-etal-2026-anything,
title = "Is There Anything More Deceptive than an Obvious Fact? Investigating Implicitness in User-Generated Argumentative Text",
author = "Sviridova, Ekaterina and
Cabrio, Elena and
Villata, Serena",
editor = "Piperidis, Stelios and
Bel, N{\'u}ria and
van den Heuvel, Henk and
Ide, Nancy and
Krek, Simon and
Toral, Antonio",
booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resource Association",
url = "https://aclanthology.org/2026.lrec-1.657/",
doi = "10.63317/48pa29hp9qoy",
pages = "8303--8316",
abstract = "While various attempts towards unveiling implicitness in argumentation have been made, particularly towards improving automatic detection and reconstruction of implicit components and background knowledge, the task remains overly challenging. In this paper, we present, to the best of our knowledge, the first fine-grained typology of implicitness in argumentation, distinguishing among implicature, ambiguity, and presupposition. Applying this typology, we annotate 78 full-length discussions from the Change My View forum, building the largest publicly available dataset of real-world enthymemes with implicitness types labeled. For comparison, we additionally annotate 112 short argumentative texts from the Microtext corpus to examine how text length and complexity influence the automatic analysis of natural arguments. Leveraging these datasets, we establish strong baselines for two tasks: (i) enthymeme detection and (ii) fine-grained implicitness classification, with both encoder-only and large language models, highlighting the challenge of modeling implicit reasoning in long, unstructured discourse."
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%0 Conference Proceedings
%T Is There Anything More Deceptive than an Obvious Fact? Investigating Implicitness in User-Generated Argumentative Text
%A Sviridova, Ekaterina
%A Cabrio, Elena
%A Villata, Serena
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F sviridova-etal-2026-anything
%X While various attempts towards unveiling implicitness in argumentation have been made, particularly towards improving automatic detection and reconstruction of implicit components and background knowledge, the task remains overly challenging. In this paper, we present, to the best of our knowledge, the first fine-grained typology of implicitness in argumentation, distinguishing among implicature, ambiguity, and presupposition. Applying this typology, we annotate 78 full-length discussions from the Change My View forum, building the largest publicly available dataset of real-world enthymemes with implicitness types labeled. For comparison, we additionally annotate 112 short argumentative texts from the Microtext corpus to examine how text length and complexity influence the automatic analysis of natural arguments. Leveraging these datasets, we establish strong baselines for two tasks: (i) enthymeme detection and (ii) fine-grained implicitness classification, with both encoder-only and large language models, highlighting the challenge of modeling implicit reasoning in long, unstructured discourse.
%R 10.63317/48pa29hp9qoy
%U https://aclanthology.org/2026.lrec-1.657/
%U https://doi.org/10.63317/48pa29hp9qoy
%P 8303-8316
Markdown (Informal)
[Is There Anything More Deceptive than an Obvious Fact? Investigating Implicitness in User-Generated Argumentative Text](https://aclanthology.org/2026.lrec-1.657/) (Sviridova et al., LREC 2026)
ACL