Papers by Benno Uthayasooriyar

2 papers
Few-shot domain adaptation for named-entity recognition via joint constrained k-means and subspace selection (2025.coling-main)

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Challenge: Named-entity recognition (NER) requires large annotated datasets, which limits its applicability across domains with varying entity definitions.
Approach: They propose a weakly-supervised algorithm that combines small labeled datasets with large amounts of unlabeled data.
Outcome: The proposed approach achieves state-of-the-art results in few-shot NER . it combines label supervision, cluster size constraints, and domain-specific discriminative subspace selection.
DocPolarBERT: A Pre-trained Model for Document Understanding with Relative Polar Coordinate Encoding of Layout Structures (2026.eacl-long)

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Challenge: Existing models that take text block positions into account are not efficient for document understanding.
Approach: They propose a layout-aware BERT model that takes into account text block positions in relative polar coordinate system rather than the Cartesian one.
Outcome: The proposed model eliminates the need for absolute positional embeddings on a dataset more than six times smaller than the widely used IIT-CDIP corpus.

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