Lifelong Event Detection via Optimal Transport Article Swipe
Viet Dao
,
Van-Cuong Pham
,
Quyen Tran
,
Thanh-Thien Le
,
Linh Ngo Van
,
Thien Huu Nguyen
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2410.08905
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2410.08905
Continual Event Detection (CED) poses a formidable challenge due to the catastrophic forgetting phenomenon, where learning new tasks (with new coming event types) hampers performance on previous ones. In this paper, we introduce a novel approach, Lifelong Event Detection via Optimal Transport (LEDOT), that leverages optimal transport principles to align the optimization of our classification module with the intrinsic nature of each class, as defined by their pre-trained language modeling. Our method integrates replay sets, prototype latent representations, and an innovative Optimal Transport component. Extensive experiments on MAVEN and ACE datasets demonstrate LEDOT's superior performance, consistently outperforming state-of-the-art baselines. The results underscore LEDOT as a pioneering solution in continual event detection, offering a more effective and nuanced approach to addressing catastrophic forgetting in evolving environments.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2410.08905
- https://arxiv.org/pdf/2410.08905
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403443733
All OpenAlex metadata
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https://openalex.org/W4403443733Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2410.08905Digital Object Identifier
- Title
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Lifelong Event Detection via Optimal TransportWork title
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preprintOpenAlex work type
- Language
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enPrimary language
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2024Year of publication
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2024-10-11Full publication date if available
- Authors
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Viet Dao, Van-Cuong Pham, Quyen Tran, Thanh-Thien Le, Linh Ngo Van, Thien Huu NguyenList of authors in order
- Landing page
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https://arxiv.org/abs/2410.08905Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2410.08905Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2410.08905Direct OA link when available
- Concepts
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Event (particle physics), Business, Computer science, Environmental science, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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