Papers by Raymond Ng
Stigma Annotation Scheme and Stigmatized Language Detection in Health-Care Discussions on Social Media (2020.lrec-1)
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| Challenge: | a large amount of research has been done on the interpretation and influence of stigma on human behaviour and health. |
| Approach: | They develop an annotation scheme and improve the annotation process for stigma identification . they aim to distinguish stigmatised language from non-stigmatised using machine learning and NLP . |
| Outcome: | The proposed method improves the annotation process for stigma identification . the results show that the method performs better than other models . |
SEA-BED: How Do Embedding Models Represent Southeast Asian Languages? (2026.acl-long)
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Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Raymond Ng, Jann Railey Montalan, Thura Aung, Jian Gang Ngui, Yosephine Susanto, William Chandra Tjhi, Panuthep Tasawong, Erik Cambria, Ekapol Chuangsuwanich, Sarana Nutanong
| Challenge: | SEA-BED examines how multilingual text embeddings perform across tasks and languages . performance gaps arise from data coverage, training objectives, and architectural design, authors say . |
| Approach: | They propose a large-scale benchmark covering 10 SEA languages and diverse embedding tasks. |
| Outcome: | The proposed model performs poorly across languages and tasks, but language-task analyses reveal inconsistencies . the results suggest that performance gaps arise from limitations in data coverage, training objectives, and architectural design. |
Discourse Analysis and Its Applications (P19-4)
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| Challenge: | Discourse processing is a suite of NLP tasks to uncover linguistic structures from texts at several levels, which can support many downstream applications. |
| Approach: | They present a set of tasks to uncover linguistic structures from texts at several levels, which can support many downstream applications. |
| Outcome: | The tutorial covers the basic concepts of discourse analysis and linguistic structures in monologue vs. conversation, synchronous v. asynchronous conversation, and key linguistic structure in discourse analysis. |
COMET-M: Reasoning about Multiple Events in Complex Sentences (2023.findings-emnlp)
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| Challenge: | Existing commonsense models that generate event-centric inferences for simple sentences struggle with the complexity of multi-event sentences prevalent in natural text. |
| Approach: | They propose a commonsense model that generates inferences for a target event within a complex sentence using a multi-event inference dataset. |
| Outcome: | The proposed model produces inferences for a target event within a complex sentence taking the complete context into account. |
What happens before and after: Multi-Event Commonsense in Event Coreference Resolution (2023.eacl-main)
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| Challenge: | Existing event coreference models cluster event mentions pertaining to the same event, but they fail to leverage commonsense inferences for lexically-divergent mentions. |
| Approach: | They propose a model that extends event mentions with temporal commonsense inferences to generate plausible events that happen before and after the target events. |
| Outcome: | The proposed model generates plausible events that happen before and after the target event, and then after it, such as "he was sentenced". |
Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation (2025.acl-long)
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Shivalika Singh, Angelika Romanou, Clémentine Fourrier, David Ifeoluwa Adelani, Jian Gang Ngui, Daniel Vila-Suero, Peerat Limkonchotiwat, Kelly Marchisio, Wei Qi Leong, Yosephine Susanto, Raymond Ng, Shayne Longpre, Sebastian Ruder, Wei-Yin Ko, Antoine Bosselut, Alice Oh, Andre Martins, Leshem Choshen, Daphne Ippolito, Enzo Ferrante, Marzieh Fadaee, Beyza Ermis, Sara Hooker
| Challenge: | Reliable multilingual evaluation is difficult and culturally appropriate evaluation is even harder to achieve. |
| Approach: | They propose a multilingual evaluation framework that aims to mitigate these biases by improving translations and annotation practices. |
| Outcome: | The proposed framework improves translation quality and cultural coverage and is culturally sensitive and culturally agnostic. |
A High Precision Pipeline for Financial Knowledge Graph Construction (2020.coling-main)
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Sarah Elhammadi, Laks V.S. Lakshmanan, Raymond Ng, Michael Simpson, Baoxing Huai, Zhefeng Wang, Lanjun Wang
| Challenge: | Knowledge graphs are a standard for structured knowledge representation in the Semantic Web. |
| Approach: | They propose to extract financial news articles into a knowledge graph by using a financial dictionary. |
| Outcome: | The proposed pipeline extracts 342,000 financial news articles with a precision of 78% at the top-100 extractions. |