arXiv · 2510.13259
Hypernetworks for Perspectivist Adaptation
Abstract
The task of perspective-aware classification introduces a bottleneck in terms of parametric efficiency that did not get enough recognition in existing studies. In this article, we aim to address this issue by applying an existing architecture, the hypernetwork+adapters combination, to perspectivist classification. Ultimately, we arrive at a solution that can compete with specialized models in adopting user perspectives on hate speech and toxicity detection, while also making use of considerably fewer parameters. Our solution is architecture-agnostic and can be applied to a wide range of base models out of the box.
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Daniil Ignatev, Denis Paperno, Massimo Poesio. 2025-10-15. Hypernetworks for Perspectivist Adaptation. https://arxiv.org/abs/2510.13259
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