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        <namePart type="given">Shivam</namePart>
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    <abstract>Analyzing the temporal sequence of texts from sources such as social media, news, and parliamentary debates is a challenging problem as it exhibits time-varying scale-free properties and fine-grained timing irregularities. We propose a Hyperbolic Hawkes Attention Network (HYPHEN), which learns a data-driven hyperbolic space and models irregular powerlaw excitations using a hyperbolic Hawkes process. Through quantitative and exploratory experiments over financial NLP, suicide ideation detection, and political debate analysis we demonstrate HYPHEN’s practical applicability for modeling online text sequences in a geometry agnostic manner.</abstract>
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%0 Conference Proceedings
%T HYPHEN: Hyperbolic Hawkes Attention For Text Streams
%A Agarwal, Shivam
%A Sawhney, Ramit
%A Ahuja, Sanchit
%A Soun, Ritesh
%A Chava, Sudheer
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F agarwal-etal-2022-hyphen
%X Analyzing the temporal sequence of texts from sources such as social media, news, and parliamentary debates is a challenging problem as it exhibits time-varying scale-free properties and fine-grained timing irregularities. We propose a Hyperbolic Hawkes Attention Network (HYPHEN), which learns a data-driven hyperbolic space and models irregular powerlaw excitations using a hyperbolic Hawkes process. Through quantitative and exploratory experiments over financial NLP, suicide ideation detection, and political debate analysis we demonstrate HYPHEN’s practical applicability for modeling online text sequences in a geometry agnostic manner.
%R 10.18653/v1/2022.acl-short.69
%U https://aclanthology.org/2022.acl-short.69
%U https://doi.org/10.18653/v1/2022.acl-short.69
%P 620-627

Markdown (Informal)

[HYPHEN: Hyperbolic Hawkes Attention For Text Streams](https://aclanthology.org/2022.acl-short.69) (Agarwal et al., ACL 2022)

• HYPHEN: Hyperbolic Hawkes Attention For Text Streams (Agarwal et al., ACL 2022)

ACL

• Shivam Agarwal, Ramit Sawhney, Sanchit Ahuja, Ritesh Soun, and Sudheer Chava. 2022. HYPHEN: Hyperbolic Hawkes Attention For Text Streams. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 620–627, Dublin, Ireland. Association for Computational Linguistics.