Lonneke Van Der Plas — accepted AI-conference papers

2025

Creative Preference Optimization

Mete Ismayilzada, Antonio Laverghetta Jr., Simone A. Luchini, Reet Patel, Antoine Bosselut, Lonneke Van Der Plas +1

EMNLP 2025

While Large Language Models (LLMs) have demonstrated impressive performance across natural language generation tasks, their ability to generate truly creative content—characterized by novelty, diversity, surprise, and quality—remains limited. Existing methods for enhancing LLM creativity often focus

Cited by 0 Source ↗PDF ↗Scholar ↗

2025

Evaluating Morphological Compositional Generalization in Large Language Models

Mete Ismayilzada, Defne Circi, Jonne Sälevä, Hale Sirin, Abdullatif Köksal, Bhuwan Dhingra +3

NAACL 2025long

Large language models (LLMs) have demonstrated significant progress in various natural language generation and understanding tasks. However, their linguistic generalization capabilities remain questionable, raising doubts about whether these models learn language similarly to humans. While humans ex…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗

2025

HintsOfTruth: A Multimodal Checkworthiness Detection Dataset with Real and Synthetic Claims

Michiel Van Der Meer, Pavel Korshunov, Sébastien Marcel, Lonneke Van Der Plas

ACL 2025long

Misinformation can be countered with fact-checking, but the process is costly and slow. Identifying checkworthy claims is the first step, where automation can help scale fact-checkers’ efforts. However, detection methods struggle with content that is (1) multimodal, (2) from diverse domains, and (3)…

Cited by 0 Source ↗PDF ↗Scholar ↗