Kosmic: Korean Text Similarity Metric Reflecting Honorific Distinctions (2024.lrec-main)
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| Challenge: | Existing methods for text similarity measurement focus on the semantic dimension, neglecting the unique linguistic attributes found in languages like Korean. |
| Approach: | They propose a Korean text-similarity metric that encompasses the semantic and tonal facets of a given text pair. |
| Outcome: | The proposed method outperforms existing methods in Korean and other languages . it identifies which methods preserve semantics and tone while preserving similarity . |
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| Challenge: | morphological richness and complex syntax of Korean cause difficulties in neural model training. |
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| Challenge: | Open Ko-LLM Leaderboard has been instrumental in benchmarking Korean Large Language Models . however, the leaderboard has faced significant limitations over time due to its academic nature . |
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Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2026.acl-demo)
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| Challenge: | ACL 2026 System Demonstration Track accepted 85 papers . one paper received Best Demo award . |
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| Challenge: | 58 papers were selected for inclusion in the program, while a small number received only two reviews. |
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Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2024.acl-demos)
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| Challenge: | ACL 2024 System Demonstration Track invites submissions describing system demonstrations . submissions will undergo a single-blind review process . |
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| Challenge: | the 58th Annual Meeting of the Association for Computational Linguistics will be held online in a virtual environment. |
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| Challenge: | 61 submissions were received for the tutorials at ACL 2026 . |
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CLIcK: A Benchmark Dataset of Cultural and Linguistic Intelligence in Korean (2024.lrec-main)
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| Challenge: | Existing benchmark datasets for Korean cultural and linguistic knowledge are derived from the English counterparts through translation, so they overlook cultural contexts. |
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