Papers by Alistair Plum
Sinhala Encoder-only Language Models and Evaluation (2025.acl-long)
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Tharindu Ranasinghe, Hansi Hettiarachchi, Nadeesha Chathurangi Naradde Vidana Pathirana, Damith Premasiri, Lasitha Uyangodage, Isuri Nanomi Arachchige, Alistair Plum, Paul Rayson, Ruslan Mitkov
| Challenge: | Recent advances in language models (LMs) have produced excellent results in many NLP tasks, but their effectiveness is highly dependent on available pre-training resources. |
| Approach: | They propose to collect the largest monolingual corpus for Sinhala and compile a benchmark and evaluate LMs on it. |
| Outcome: | The proposed language models outperform the popular multilingual LMs in downstream NLP tasks. |
Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Language (2024.lrec-main)
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| Challenge: | Existing methods to extract relationships are limited to English and require annotating datasets in order to be expensive and time-consuming. |
| Approach: | They apply guided distant supervision to create a large biographical relationship extraction dataset for German using 80,000 instances for nine relationship types. |
| Outcome: | The proposed dataset is the largest biographical German relationship extraction dataset. |
ltzGLUE: Luxembourgish General Language Understanding Evaluation (2026.findings-acl)
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Alistair Plum, Felicia Körner, Anne-Marie Lutgen, Laura Bernardy, Fred Philippy, Emilia Milano, Nils Rehlinger, Cedric Lothritz, Tharindu Ranasinghe, Barbara Plank, Christoph Purschke
| Challenge: | ltzGLUE is the first official NLU benchmark for Luxembourgish (LTZ) based on the popular GLUE benchmark for English. |
| Approach: | They propose a new natural language understanding (NLU) benchmark for Luxembourgish based on the popular GLUE benchmark for English. |
| Outcome: | The proposed model performs well across many languages and is based on the GLUE benchmark for English. |