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• Fiona Anting Tan, Sujatha Das Gollapalli, and See-Kiong Ng. 2021. NUS-IDS at CASE 2021 Task 1: Improving Multilingual Event Sentence Coreference Identification With Linguistic Information. In Proceedings of the 4th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021), pages 105–112, Online. Association for Computational Linguistics. https://aclanthology.org/2021.case-1.14 Permalink
• Fiona Anting Tan and See-Kiong Ng. 2021. NUS-IDS at FinCausal 2021: Dependency Tree in Graph Neural Network for Better Cause-Effect Span Detection. In Proceedings of the 3rd Financial Narrative Processing Workshop, pages 37–43, Lancaster, United Kingdom. Association for Computational Linguistics. https://aclanthology.org/2021.fnp-1.6 Permalink
• Fiona Anting Tan, Devamanyu Hazarika, See-Kiong Ng, Soujanya Poria, and Roger Zimmermann. Causal augmentation for causal sentence classification. In Proceedings of the First Workshop on Causal Inference and NLP, pages 1–20, Punta Cana, Dominican Republic, November 2021. Association for Computational Linguistics. doi: 10.18653/v1/2021.cinlp-1.1. https://aclanthology.org/2021.cinlp-1.1 Permalink
• Fiona Anting Tan, Ali Hürriyetoglu, Tommaso Caselli, Nelleke Oostdijk, Tadashi Nomoto, Hansi Hettiarachchi, Iqra Ameer, Onur Uca, Farhana Ferdousi Liza, and Tiancheng Hu. 2022. The Causal News Corpus: Annotating Causal Relations in Event Sentences from News. In Proceedings of the 13th Language Resources and Evaluation Conference, Marseille, France. European Language Resources Association. https://aclanthology.org/2022.lrec-1.246/ Permalink
• Fiona Anting Tan, Hansi Hettiarachchi, Ali Hürriyetoglu, Tommaso Caselli, Onur Uca, Farhana Ferdousi Liza, and Nelleke Oostdijk. 2022. Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2022. In Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE), pages 195–208, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics. https://aclanthology.org/2022.case-1.28 Permalink
• Fiona Anting Tan, Debdeep Paul, Sahim Yamaura, Miura Koji, and See-Kiong Ng. 2023. Constructing and interpreting causal knowledge graphs from news. In Proceedings of the AAAI Summer Symposium on AI for FinTech. Singapore, Singapore. https://ojs.aaai.org/index.php/AAAI-SS/article/view/27476 Permalink
• Fiona Anting Tan, Xinyu Zuo, and See-Kiong Ng. 2023. UniCausal: Unified benchmark and repository for causal text mining. In Big Data Analytics and Knowledge Discovery, pages 248–262, Cham. Springer Nature Switzerland. https://link.springer.com/chapter/10.1007/978-3-031-39831-5_23 Permalink
• Fiona Anting Tan, Hansi Hettiarachchi, Ali Hürriyetoglu, Nelleke Oostdijk, Onur Uca, Surendrabikram Thapa, and Farhana Ferdousi Liza. 2023. Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2023. In Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE), Varna, Bulgaria (Hybrid). Association for Computational Linguistics. https://aclanthology.org/2023.case-1.19/ Permalink
• Fiona Anting Tan and See-Kiong Ng. 2023. Economics assistant for robustness checks (EconARC): Identifying confounders from causal knowledge graphs. In The Semantic Web - ISWC 2023 - 22nd International Semantic Web Conference, November 6-10, 2023, Proceedings, Lecture Notes in Computer Science. Springer. https://hozo.jp/ISWC2023_PD-Industry-proc/ISWC2023_paper_414.pdf Permalink
• Fiona Anting Tan, Hansi Hettiarachchi, Ali Hürriyetoglu, Nelleke Oostdijk, Tommaso Caselli, Tadashi Nomoto, Onur Uca, Farhana Ferdousi Liza, and See-Kiong Ng. 2023. RECESS: Resource for extracting cause, effect, and signal spans. In Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, Bali, Indonesia. Association for Computational Linguistics. https://aclanthology.org/2023.ijcnlp-main.6.pdf Permalink
• Tan, F. A. (2024). To Know the Causes of Things: Text Mining for Causal Relations. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23425-23426. https://doi.org/10.1609/aaai.v38i21.30413 https://ojs.aaai.org/index.php/AAAI/article/view/30413 Permalink