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20232026
most citedUnderstanding the effects of language-specific class imbalance in multilingual fine-tuning

2 citations · 7 across the 10 of their papers we have counts for

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cs.CL2026

CresOWLve: Benchmarking Creative Problem-Solving Over Real-World Knowledge

Mete Ismayilzada, Renqing Cuomao, Daniil Yurshevich +3

Creative problem-solving requires combining multiple cognitive abilities, including logical reasoning, lateral thinking, analogy-making, and commonsense knowledge, to discover insi…

cs.CL2026

Binary Token-Level Classification with DeBERTa for All-Type MWE Identification: A Lightweight Approach with Linguistic Enhancement

Diego Rossini, Lonneke van der Plas

We present a comprehensive approach for multiword expression (MWE) identification that combines binary token-level classification, linguistic feature integration, and data augmenta…

cs.CL2025★ 1 cited

Creative Preference Optimization

Mete Ismayilzada, Antonio Laverghetta, Simone A. Luchini +4

While Large Language Models (LLMs) have demonstrated impressive performance across natural language generation tasks, their ability to generate truly creative content-characterized…

cs.CL2024★ 2 cited

Evaluating Creative Short Story Generation in Humans and Large Language Models

Mete Ismayilzada, Claire Stevenson, Lonneke van der Plas

Story-writing is a fundamental aspect of human imagination, relying heavily on creativity to produce narratives that are novel, effective, and surprising. While large language mode…

cs.CL2024

Evaluating Morphological Compositional Generalization in Large Language Models

Mete Ismayilzada, Defne Circi, Jonne Sälevä +6

Large language models (LLMs) have demonstrated significant progress in various natural language generation and understanding tasks. However, their linguistic generalization capabil…

cs.CL2024★ 2 cited

Understanding the effects of language-specific class imbalance in multilingual fine-tuning

Vincent Jung, Lonneke van der Plas

We study the effect of one type of imbalance often present in real-life multilingual classification datasets: an uneven distribution of labels across languages. We show evidence th…

cs.CL2023

Can language models learn analogical reasoning? Investigating training objectives and comparisons to human performance

Molly R. Petersen, Lonneke van der Plas

While analogies are a common way to evaluate word embeddings in NLP, it is also of interest to investigate whether or not analogical reasoning is a task in itself that can be learn…