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        <title>Auxiliary tasks to boost Biaffine Semantic Dependency Parsing</title>
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        <name type="personal">
            <namePart type="given">Preslav</namePart>
            <namePart type="family">Nakov</namePart>
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        <name type="personal">
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            <namePart type="family">Villavicencio</namePart>
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    <abstract>The biaffine parser of (CITATION) was successfully extended to semantic dependency parsing (SDP) (CITATION). Its performance on graphs is surprisingly high given that, without the constraint of producing a tree, all arcs for a given sentence are predicted independently from each other (modulo a shared representation of tokens).To circumvent such an independence of decision, while retaining the O(n²) complexity and highly parallelizable architecture, we propose to use simple auxiliary tasks that introduce some form of interdependence between arcs. Experiments on the three English acyclic datasets of SemEval-2015 task 18 (CITATION), and on French deep syntactic cyclic graphs (CITATION) show modest but systematic performance gains on a near-state-of-the-art baseline using transformer-based contextualized representations. This provides a simple and robust method to boost SDP performance.</abstract>
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%0 Conference Proceedings
%T Auxiliary tasks to boost Biaffine Semantic Dependency Parsing
%A Candito, Marie
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Findings of the Association for Computational Linguistics: ACL 2022
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F candito-2022-auxiliary
%X The biaffine parser of (CITATION) was successfully extended to semantic dependency parsing (SDP) (CITATION). Its performance on graphs is surprisingly high given that, without the constraint of producing a tree, all arcs for a given sentence are predicted independently from each other (modulo a shared representation of tokens).To circumvent such an independence of decision, while retaining the O(n²) complexity and highly parallelizable architecture, we propose to use simple auxiliary tasks that introduce some form of interdependence between arcs. Experiments on the three English acyclic datasets of SemEval-2015 task 18 (CITATION), and on French deep syntactic cyclic graphs (CITATION) show modest but systematic performance gains on a near-state-of-the-art baseline using transformer-based contextualized representations. This provides a simple and robust method to boost SDP performance.
%R 10.18653/v1/2022.findings-acl.190
%U https://aclanthology.org/2022.findings-acl.190
%U https://doi.org/10.18653/v1/2022.findings-acl.190
%P 2422-2429

Markdown (Informal)

[Auxiliary tasks to boost Biaffine Semantic Dependency Parsing](https://aclanthology.org/2022.findings-acl.190) (Candito, Findings 2022)

• Auxiliary tasks to boost Biaffine Semantic Dependency Parsing (Candito, Findings 2022)

ACL

• Marie Candito. 2022. Auxiliary tasks to boost Biaffine Semantic Dependency Parsing. In Findings of the Association for Computational Linguistics: ACL 2022, pages 2422–2429, Dublin, Ireland. Association for Computational Linguistics.