@inproceedings{tseriotou-etal-2024-sig,
title = "Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling",
author = "Tseriotou, Talia and
Chan, Ryan and
Tsakalidis, Adam and
Bilal, Iman Munire and
Kochkina, Elena and
Lyons, Terry and
Liakata, Maria",
editor = "Aletras, Nikolaos and
De Clercq, Orphee",
booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.eacl-demo.24",
pages = "223--237",
abstract = "We present an open-source, pip installable toolkit, Sig-Networks, the first of its kind for longitudinal language modelling. A central focus is the incorporation of Signature-based Neural Network models, which have recently shown success in temporal tasks. We apply and extend published research providing a full suite of signature-based models. Their components can be used as PyTorch building blocks in future architectures. Sig-Networks enables task-agnostic dataset plug-in, seamless preprocessing for sequential data, parameter flexibility, automated tuning across a range of models. We examine signature networks under three different NLP tasks of varying temporal granularity: counselling conversations, rumour stance switch and mood changes in social media threads, showing SOTA performance in all three, and provide guidance for future tasks. We release the Toolkit as a PyTorch package with an introductory video, Git repositories for preprocessing and modelling including sample notebooks on the modeled NLP tasks.",
}
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%0 Conference Proceedings
%T Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling
%A Tseriotou, Talia
%A Chan, Ryan
%A Tsakalidis, Adam
%A Bilal, Iman Munire
%A Kochkina, Elena
%A Lyons, Terry
%A Liakata, Maria
%Y Aletras, Nikolaos
%Y De Clercq, Orphee
%S Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F tseriotou-etal-2024-sig
%X We present an open-source, pip installable toolkit, Sig-Networks, the first of its kind for longitudinal language modelling. A central focus is the incorporation of Signature-based Neural Network models, which have recently shown success in temporal tasks. We apply and extend published research providing a full suite of signature-based models. Their components can be used as PyTorch building blocks in future architectures. Sig-Networks enables task-agnostic dataset plug-in, seamless preprocessing for sequential data, parameter flexibility, automated tuning across a range of models. We examine signature networks under three different NLP tasks of varying temporal granularity: counselling conversations, rumour stance switch and mood changes in social media threads, showing SOTA performance in all three, and provide guidance for future tasks. We release the Toolkit as a PyTorch package with an introductory video, Git repositories for preprocessing and modelling including sample notebooks on the modeled NLP tasks.
%U https://aclanthology.org/2024.eacl-demo.24
%P 223-237
Markdown (Informal)
[Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling](https://aclanthology.org/2024.eacl-demo.24) (Tseriotou et al., EACL 2024)
ACL
- Talia Tseriotou, Ryan Chan, Adam Tsakalidis, Iman Munire Bilal, Elena Kochkina, Terry Lyons, and Maria Liakata. 2024. Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 223–237, St. Julians, Malta. Association for Computational Linguistics.