| Challenge: | Existing methods to remove sentences consisting of illegal characters are tedious and repetitive. |
| Approach: | They propose a statistical method to identify illegal characters in natural language processing . they use a fixed-size feature vector to generate a Gaussian mixture model for each sentence . |
| Outcome: | The proposed method can score sentences and filter corpus on clean corpus and improve performance. |
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| Challenge: | a high quality web corpus is essential for large language models to be developed . strong filtering methods can lead to lesser performance in downstream tasks . |
| Approach: | They build classifiers and language models that can process large amounts of corpora quickly enough for pretraining LLMs. |
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NESTLE: a No-Code Tool for Statistical Analysis of Legal Corpus (2024.eacl-demo)
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| Challenge: | a comprehensive statistical analysis of legal corpus requires specialized tools or programming skills. |
| Approach: | They propose a no-code tool for large-scale statistical analysis of legal corpus . NESTLE can extract any type of information that has not been predefined in the IE system . |
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Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts (2020.emnlp-tutorials)
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| Challenge: | EMNLP tutorials session in 2020 will feature cutting-edge and introductory topics . review committees evaluated tutorial proposals on clarity, preparedness, novelty, timeliness, likely audience, open access to the teaching materials and compatibility of preferred venues. |
| Approach: | EMNLP tutorials session in 2020 will feature cutting-edge and introductory topics . review committees evaluated tutorial proposals on clarity, preparedness, novelty, timeliness and likely audience . |
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Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Tutorial Abstracts (2021.acl-tutorials)
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| Challenge: | . - (EN) |
| Approach: | . - (EN) |
| Outcome: | . - (EN) |
Treebank Embedding Vectors for Out-of-Domain Dependency Parsing (2020.acl-main)
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| Challenge: | a recent advance in monolingual dependency parsing is the idea of a treebank embedding vector . this allows the model to prefer training data from one treebank over another at test time . |
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Semantic Frame Induction from a Real-World Corpus (2025.acl-srw)
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| Challenge: | Existing studies on semantic frame induction have demonstrated that pre-trained language models (PLMs) have led to more accurate results. |
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Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts (2021.emnlp-tutorials)
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| Challenge: | EMNLP tutorials are lecture-based presentations that are presented at conferences around the world. |
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NAG-NER: a Unified Non-Autoregressive Generation Framework for Various NER Tasks (2023.acl-industry)
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Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations (D19-3)
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How Universal are Universal Dependencies? Exploiting Syntax for Multilingual Clause-level Sentiment Detection (2020.lrec-1)
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| Challenge: | a new method for clause-level sentiment detection is proposed for multilingual use cases. |
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