Papers with human evaluator

3 papers
Leveraging syntactic parsing to improve event annotation matching (D19-59)

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Challenge: Evaluating annotator consistency is crucial when building datasets for mention detection.
Approach: They propose to use different fuzzy-matching functions to resolve this ambiguity by extracting syntactic heads present in annotations and using the Dice coefficient to measure similarity between sets.
Outcome: The proposed functions are tested against the judgment of a human evaluator and show that the best-performing function agrees with the human .
Early-Exit and Instant Confidence Translation Quality Estimation (2026.eacl-long)

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Challenge: Quality estimation models are often opaque and computationally expensive, making them impractical to be part of large-scale pipelines.
Approach: They propose an uncertainty-aware quality estimation model that matches previous approaches at a fraction of their costs.
Outcome: The proposed method reduces evaluation costs by 50% and improves reranking performance.
A Bayesian Topic Model for Human-Evaluated Interpretability (2022.lrec-1)

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Challenge: Topic modeling is an effective way to analyze unstructured textual data.
Approach: They propose to combine nonparametric and weakly-supervised topic models to produce interpretable topics.
Outcome: The proposed model outperforms weakly-supervised models in the field of topic modeling.

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