🏙️ Works of Randstad from 2026

12 works · the most cited first · ← Randstad

1. Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error AnnotationsFindings of the Association for Computational LinguisticsShaomu Tan, Ryosuke Mitani, Ritvik Choudhary, et al.2026 · 2 citations
2. A framework for annotating and modelling intentions behind metaphor useJoint Conference on Lexical and Computational Semantics (*SEM)Gianluca Michelli, Xiaoyu Tong, Ekaterina Shutova2026 · 1 citation
3. Human-like Fleeting Memory Improves Language Learning but Impairs Reading Time Prediction in Transformer Language ModelsTransactions of the Association for Computational Linguistics (TACL)Abishek Thamma, Micha Heilbron2026 · 1 citation
4. Plan-Guided Text Simplification with Extended ContextsJoint Workshop on Readability and Text Simplification (READIxTSAR) @ LRECPascal Mathas, Jan Bakker, Jaap Kamps2026 · 1 citation
5. SimLex-999 for Modern GreekSIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered LanguagesLeonidas Mylonadis, Jelke Bloem2026 · 1 citation
6. Transparent Semantic Change Detection with Dependency-Based ProfilesProceedings for the International Workshop on Computational Approaches to Language ChangeBach Phan Tat, Kris Heylen, Dirk Geeraerts, et al.2026 · 1 citation
7. Assessing Small Language Models as Text Simplification EvaluatorsWorkshop on Evaluating Text Difficulty in a Multilingual ContextDavid Carranza Navarrete, Jan Bakker, Jaap Kamps2026
8. Breaking the Script: Do Role-Playing Agents Maintain Goal Alignment under Distraction?Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)Dongxu Lu, Albert Gatt, Johan Jeuring2026
9. Examining Algebraic Recombination for Compositional GeneralisationWorkshop on Cognitive Modeling and Computational Linguistics (CMCL)Joaquin Cardona Ruiz, Antske Fokkens, Lucia Donatelli2026
10. Lost in Translation: Repurposing semantic similarity benchmarks for evaluating lexical-semantic consistency in LLM-based machine translationWorkshop on Resources and Representations for Under-Resourced Languages and DomainsQuin Ye, Jelke Bloem2026
11. Mimicking Neural Machine Translation History for Pedagogic ReasonsInternational Workshop on Teaching AI-Based Translation and TechnologiesVincent Vandeghinste2026
12. Smarter edits? Post-editing with error highlights and translation suggestionsAnnual Conference of the European Association for Machine Translation (EAMT)Fleur V.J. van Tellingen, Gautam Ranka, Dora Žugčić, et al.2026

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