Papers by Andrew Koh
Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences (2020.findings-emnlp)
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| Challenge: | Existing studies have used pre-trained language models for domain adaptation or transfer learning to improve natural language processing performance. |
| Approach: | They propose to fine-tune word sense disambiguation on sequence-pair ranking task and to use existing WordNet examples to augment the model. |
| Outcome: | The proposed model achieves state-of-the-art on the English all-words benchmark datasets. |
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models (2024.lrec-main)
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Oana Ignat, Zhijing Jin, Artem Abzaliev, Laura Biester, Santiago Castro, Naihao Deng, Xinyi Gao, Aylin Ece Gunal, Jacky He, Ashkan Kazemi, Muhammad Khalifa, Namho Koh, Andrew Lee, Siyang Liu, Do June Min, Shinka Mori, Joan C. Nwatu, Veronica Perez-Rosas, Siqi Shen, Zekun Wang, Winston Wu, Rada Mihalcea
| Challenge: | Recent advances in large language models have led to misleading public discourse that “it’s all been solved.” |
| Approach: | They identify 14 research areas encompassing 45 research directions that require new research and are not directly solvable by LLMs. |
| Outcome: | The research areas identified are 45 research directions that require new research and are not directly solvable by LLMs. |