Papers by Hansi Hettiarachchi
NSina: A News Corpus for Sinhala (2024.lrec-main)
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Hansi Hettiarachchi, Damith Premasiri, Lasitha Randunu Chandrakantha Uyangodage, Tharindu Ranasinghe
| Challenge: | introducing large language models (LLMs) has advanced natural language processing (NLP), but their effectiveness is largely dependent on pre-training resources. |
| Approach: | They propose a large news corpus for Sinhala with a set of NLP tasks for the language . NSina is the largest news corpuse for Sinha, available up to date . |
| Outcome: | The proposed model outperforms existing models in many benchmarks and outperformed previous models in high-resource languages. |
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. |
MUSTS: MUltilingual Semantic Textual Similarity Benchmark (2025.acl-short)
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| Challenge: | Existing benchmarks for semantic textual similarity (STS) are limited to high-resource languages and do not include datasets annotated focusing on relatedness instead of similarity. |
| Approach: | They propose to evaluate multilingual semantic textual similarity benchmarks which span 13 languages and annotated datasets to evaluate and compare them. |
| Outcome: | The proposed method is the most comprehensive benchmark of multilingual STS methods. |
The Causal News Corpus: Annotating Causal Relations in Event Sentences from News (2022.lrec-1)
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Fiona Anting Tan, Ali Hürriyetoğlu, Tommaso Caselli, Nelleke Oostdijk, Tadashi Nomoto, Hansi Hettiarachchi, Iqra Ameer, Onur Uca, Farhana Ferdousi Liza, Tiancheng Hu
| Challenge: | Existing annotation guidelines for event causality focus on only explicit relations or clauses. |
| Approach: | They propose an annotation schema for event causality that addresses these concerns . they annotated 3,559 event sentences from protest event news with labels on whether it contains causal relations or not. |
| Outcome: | The proposed annotation schema for event causality addresses these concerns . it performs well with 81.20% F1 score on test set and 83.46% in 5-folds cross-validation . |