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\n\n \n \n \n \n \n \n WordNet under scrutiny: Dictionary examples in the era of large language models.\n \n \n \n \n\n\n \n Almeman, F. Y.; Schockaert, S.; and Espinosa Anke, L.\n\n\n \n\n\n\n In Calzolari, N.; Kan, M.; Hoste, V.; Lenci, A.; Sakti, S.; and Xue, N., editor(s),
Proc. of LREC-COLING, 2024. \n
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@inproceedings{almeman-24,\n\ttitle = {{WordNet} under scrutiny: {D}ictionary examples in the era of large language models},\n\turl = {https://aclanthology.org/2024.lrec-main.1538},\n\tbooktitle = {Proc. of {LREC-COLING}},\n\tauthor = {Almeman, Fatemah Yousef and Schockaert, Steven and Espinosa Anke, Luis},\n\teditor = {Calzolari, Nicoletta and Kan, {Min-Yen} and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen},\n\tyear = {2024}\n}
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\n\n \n \n \n \n \n \n A benchmark for learning to translate a new language from one grammar book.\n \n \n \n \n\n\n \n Tanzer, G.; Suzgun, M.; Visser, E.; Jurafsky, D.; and Melas-Kyriazi, L.\n\n\n \n\n\n\n February 2024.\n
arXiv:2309.16575 [cs]\n\n
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@misc{tanzer-24,\n\ttitle = {A benchmark for learning to translate a new language from one grammar book},\n\turl = {http://arxiv.org/abs/2309.16575},\n\tpublisher = {{arXiv}},\n\tauthor = {Tanzer, Garrett and Suzgun, Mirac and Visser, Eline and Jurafsky, Dan and {Melas-Kyriazi}, Luke},\n\tmonth = feb,\n\tyear = {2024},\n\tnote = {{arXiv}:2309.16575 [cs]}\n}
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\n\n \n \n \n \n \n \n AMenDeD: Modelling concepts by aligning mentions, definitions and decontextualised embeddings.\n \n \n \n \n\n\n \n Gajbhiye, A.; Bouraoui, Z.; Espinosa Anke, L.; and Schockaert, S.\n\n\n \n\n\n\n In Calzolari, N.; Kan, M.; Hoste, V.; Lenci, A.; Sakti, S.; and Xue, N., editor(s),
Proc. of LREC-COLING, 2024. \n
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@inproceedings{gajbhiye-24,\n\ttitle = {{AMenDeD}: {M}odelling concepts by aligning mentions, definitions and decontextualised embeddings},\n\turl = {https://aclanthology.org/2024.lrec-main.72},\n\tbooktitle = {Proc. of {LREC-COLING}},\n\tauthor = {Gajbhiye, Amit and Bouraoui, Zied and Espinosa Anke, Luis and Schockaert, Steven},\n\teditor = {Calzolari, Nicoletta and Kan, {Min-Yen} and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen},\n\tyear = {2024}\n}
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\n\n \n \n \n \n \n \n Tailored definitions with easy reach: complexity-controllable definition generation.\n \n \n \n \n\n\n \n Yang, L.; Yuan, J.; Kong, C.; Yu, J.; Chong, R.; Liu, Z.; and Yang, E.\n\n\n \n\n\n\n
IEEE Transactions on Big Data,1–12. 2024.\n
Conference Name: IEEE Transactions on Big Data\n\n
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@article{yang-24,\n\ttitle = {Tailored definitions with easy reach: complexity-controllable definition generation},\n\turl = {https://ieeexplore.ieee.org/abstract/document/10816507},\n\tjournal = {{IEEE} Transactions on Big Data},\n\tauthor = {Yang, Liner and Yuan, Jiaxin and Kong, Cunliang and Yu, Jingsi and Chong, Ruining and Liu, Zhenghao and Yang, Erhong},\n\tyear = {2024},\n\tnote = {Conference Name: {IEEE} Transactions on Big Data},\n\tpages = {1--12}\n}
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\n\n \n \n \n \n \n \n ModeLing: a novel dataset for testing linguistic reasoning in language models.\n \n \n \n \n\n\n \n Chi, N.; Malchev, T.; Kong, R.; Chi, R.; Huang, L.; Chi, E.; McCoy, R.; and Radev, D.\n\n\n \n\n\n\n In Hahn, M.; Sorokin, A.; Kumar, R.; Shcherbakov, A.; Otmakhova, Y.; Yang, J.; Serikov, O.; Rani, P.; Ponti, E. M.; Muradoğlu, S.; Gao, R.; Cotterell, R.; and Vylomova, E., editor(s),
Proc. of the 6th Workshop on Research in Computational Linguistic Typology and Multilingual NLP, 2024. \n
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@inproceedings{chi-24,\n\ttitle = {{ModeLing}: a novel dataset for testing linguistic reasoning in language models},\n\turl = {https://aclanthology.org/2024.sigtyp-1.14/},\n\tbooktitle = {Proc. of the 6th Workshop on Research in Computational Linguistic Typology and Multilingual {NLP}},\n\tauthor = {Chi, Nathan and Malchev, Teodor and Kong, Riley and Chi, Ryan and Huang, Lucas and Chi, Ethan and {McCoy}, R. and Radev, Dragomir},\n\teditor = {Hahn, Michael and Sorokin, Alexey and Kumar, Ritesh and Shcherbakov, Andreas and Otmakhova, Yulia and Yang, Jinrui and Serikov, Oleg and Rani, Priya and Ponti, Edoardo M. and Muradoğlu, Saliha and Gao, Rena and Cotterell, Ryan and Vylomova, Ekaterina},\n\tyear = {2024}\n}
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\n\n \n \n \n \n \n \n Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book?.\n \n \n \n \n\n\n \n Aycock, S.; Stap, D.; Wu, D.; Monz, C.; and Sima'an, K.\n\n\n \n\n\n\n September 2024.\n
arXiv:2409.19151 [cs]\n\n
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@misc{aycock-24,\n\ttitle = {Can {LLMs} {R}eally {L}earn to {T}ranslate a {Low-Resource} {L}anguage from {O}ne {G}rammar {B}ook?},\n\turl = {http://arxiv.org/abs/2409.19151},\n\tpublisher = {{arXiv}},\n\tauthor = {Aycock, Seth and Stap, David and Wu, Di and Monz, Christof and Sima'an, Khalil},\n\tmonth = sep,\n\tyear = {2024},\n\tnote = {{arXiv}:2409.19151 [cs]}\n}\n
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\n\n \n \n \n \n \n \n To Ask LLMs about English Grammaticality, Prompt Them in a Different Language.\n \n \n \n \n\n\n \n Behzad, S.; Zeldes, A.; and Schneider, N.\n\n\n \n\n\n\n In Al-Onaizan, Y.; Bansal, M.; and Chen, Y., editor(s),
Findings of the Association for Computational Linguistics: EMNLP 2024, pages 15622–15634, Miami, Florida, USA, November 2024. Association for Computational Linguistics\n
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@inproceedings{behzad-etal-2024-ask,\n title = "To Ask {LLM}s about {E}nglish Grammaticality, Prompt Them in a Different Language",\n author = "Behzad, Shabnam and\n Zeldes, Amir and\n Schneider, Nathan",\n editor = "Al-Onaizan, Yaser and\n Bansal, Mohit and\n Chen, Yun-Nung",\n booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",\n month = nov,\n year = "2024",\n address = "Miami, Florida, USA",\n publisher = "Association for Computational Linguistics",\n url = "https://aclanthology.org/2024.findings-emnlp.916/",\n doi = "10.18653/v1/2024.findings-emnlp.916",\n pages = "15622--15634",\n abstract = "In addition to asking questions about facts in the world, some internet users{---}in particular, second language learners{---}ask questions about language itself. Depending on their proficiency level and audience, they may pose these questions in an L1 (first language) or an L2 (second language). We investigate how multilingual LLMs perform at crosslingual metalinguistic question answering. Focusing on binary questions about sentence grammaticality constructed from error-annotated learner corpora, we prompt three LLMs (Aya, Llama, and GPT) in multiple languages, including English, German, Korean, Russian, and Ukrainian. Our study reveals that the language of the prompt can significantly affect model performance, and despite English being the dominant training language for all three models, prompting in a different language with questions about English often yields better results."\n}\n
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\n In addition to asking questions about facts in the world, some internet users—in particular, second language learners—ask questions about language itself. Depending on their proficiency level and audience, they may pose these questions in an L1 (first language) or an L2 (second language). We investigate how multilingual LLMs perform at crosslingual metalinguistic question answering. Focusing on binary questions about sentence grammaticality constructed from error-annotated learner corpora, we prompt three LLMs (Aya, Llama, and GPT) in multiple languages, including English, German, Korean, Russian, and Ukrainian. Our study reveals that the language of the prompt can significantly affect model performance, and despite English being the dominant training language for all three models, prompting in a different language with questions about English often yields better results.\n
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