Papers by Anna Wegmann

3 papers
Does It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework (2021.emnlp-main)

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Challenge: linguistic style is an integral part of natural language, but evaluation methods for style measures are rare, often task-specific and usually do not control for content.
Approach: They propose a modular, fine-grained and content-controlled similarity-based STyle EvaLuation framework to test the performance of any model that can compare two sentences on style.
Outcome: The proposed model outperforms simple versions of commonly used style measures like 3-grams, punctuation frequency and LIWC-based approaches.
Tokenization is Sensitive to Language Variation (2025.findings-acl)

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Challenge: Variation in language is often linked to regional, social, and contextual factors.
Approach: They propose a method to estimate tokenizer impact on downstream LLM performance . they pre-train BERT models with the popular Byte-Pair Encoding algorithm .
Outcome: The proposed model improves on Rényi efficiency and other metrics on language variation.
What’s Mine becomes Yours: Defining, Annotating and Detecting Context-Dependent Paraphrases in News Interview Dialogs (2024.emnlp-main)

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Challenge: a dataset of utterance pairs from NPR and CNN is used to classify paraphrases in dialog.
Approach: They propose a dataset annotated for context-dependent paraphrases and develop a training for crowd-workers to classify paraphrase in dialog.
Outcome: The proposed dataset contains 5,581 annotations on 600 utterance pairs.

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