5 papers
On the Interplay between Human Label Variation and Model Fairness
Kemal Kurniawan, Meladel Mistica, Timothy Baldwin +1
The impact of human label variation (HLV) on model fairness is an unexplored topic. This paper examines the interplay by comparing training on majority-vote labels with a range of…
A Joint Multitask Model for Morpho-Syntactic Parsing
Demian Inostroza, Mel Mistica, Ekaterina Vylomova +2
We present a joint multitask model for the UniDive 2025 Morpho-Syntactic Parsing shared task, where systems predict both morphological and syntactic analyses following novel UD ann…
Training and Evaluating with Human Label Variation: An Empirical Study
Kemal Kurniawan, Meladel Mistica, Timothy Baldwin +1
Human label variation (HLV) challenges the standard assumption that a labelled instance has a single ground truth, instead embracing the natural variation in human annotation to tr…
To Aggregate or Not to Aggregate. That is the Question: A Case Study on Annotation Subjectivity in Span Prediction
Kemal Kurniawan, Meladel Mistica, Timothy Baldwin +1
This paper explores the task of automatic prediction of text spans in a legal problem description that support a legal area label. We use a corpus of problem descriptions written b…
Evaluating Document Coherence Modelling
Aili Shen, Meladel Mistica, Bahar Salehi +3
While pretrained language models ("LM") have driven impressive gains over morpho-syntactic and semantic tasks, their ability to model discourse and pragmatic phenomena is less clea…