Papers by Vilhjálmur Vilhjálmsson

1 papers
Semantic Outlier Removal with Embedding Models and LLMs (2025.acl-industry)

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Challenge: Modern text processing pipelines require robust methods to remove extraneous content while preserving a document’s core message.
Approach: They propose a method that leverages multilingual sentence embeddings and approximate nearest-neighbor search to identify and excise unwanted text segments.
Outcome: Experiments on HTML datasets show that SORE outperforms structural methods and yields high precision in diverse scenarios.

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