Boosting LLM performance with generative question-answer pairs via Wh‑transformation

References

1. Chen, Shuangshuang
   2024 Resolving Chinese anaphora with Chatgpt. Proceedings of the 2024 International Conference on Asian Language Processing (IALP), ed. byRui Liu, Lei Wang, Feilong Bao, Yanfeng Lu, Cunhang Fan and Minghui Dong, –. New York: Institute of Electrical and Electronics Engineers. 10.1109/IALP63756.2024.10661112
   https://doi.org/10.1109/IALP63756.2024.10661112 [Google Scholar]
2. Cheng, Lai-Shen, Lisa
   1991 On the Typology of Wh-questions. Doctoral Dissertation, Massachusetts Institute of Technology, Cambridge, MA.
   [Google Scholar]
3. Chomsky, Noam
   1957 Syntactic Structures. The Hague, Netherlands: Mouton. 10.1515/9783112316009
   https://doi.org/10.1515/9783112316009
4. Chomsky, Noam
   1970 Remarks on nominalization. Readings in English Transformational Grammar, ed. byRoderick Jacobs and Peter Rosenbaum, –. Washington, D.C.: Georgetown UP.
   [Google Scholar]
5. Chomsky, Noam
   1973 Conditions on transformations. A Festschrift for Morris Halle, ed. byStephen R. Anderson and Paul Kiparsky, –. New York: Holt, Rinehart & Winston.
   [Google Scholar]
6. Chomsky, Noam
   1993 A Minimalist Program for Linguistic Theory. Cambridge, MA: The MIT Press.
7. Chowdhury, Arijit Ghosh, and Aman Chadha
   2024 Generative data augmentation using LLMs improves distributional robustness in question answering. Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop, ed. byNeele Falk, Sara Papi and Mike Zhang, –. Stroudsburg, PA: Association for Computational Linguistics. 10.18653/v1/2024.eacl‑srw.20
   https://doi.org/10.18653/v1/2024.eacl-srw.20 [Google Scholar]
8. Chung, Meng-Hsuan, and Chao-Ting Tim Chou
   2025 Climbing towards the NLU of the universal reading of shei ‘who’. Concentric.:–. 10.1075/consl.24041.chu
   https://doi.org/10.1075/consl.24041.chu [Google Scholar]
9. Huang, Cheng-Teh James
   1982 Logical Relations in Chinese and the Theory of Grammar. Doctoral Dissertation, Massachusetts Institute of Technology, Cambridge, MA.
   [Google Scholar]
10. Jackendoff, Ray
    1977 X-bar Syntax: A Study of Phrase Structure. Cambridge, MA: The MIT Press.
11. Li, Aijun
    2002, Chinese prosody and prosodic labeling of spontaneous speech. Proceedings of Speech Prosody 2002, ed. byBernard Bel and Isabelle Marlien, –. Aix-en-Provence, France: Laboratoire Parole et Langage, Université de Provence. 10.21437/SpeechProsody.2002‑6
    https://doi.org/10.21437/SpeechProsody.2002-6 [Google Scholar]
12. Li, Shengnan, Qu Weiguang, Wei Tingxin, Zhou Junsheng, Gu Yanhui, and Li Bin
    2021 A survey of Chinese anaphora resolution. Artificial Intelligence and Security: 7th International Conference (ICAIS 2021), ed. byXingming Sun, Xiaorui Zhang, Zhihua Xia and Elisa Bertino, –. Dublin, Ireland: Springer International Publishing. 10.1007/978‑3‑030‑78609‑0_16
    https://doi.org/10.1007/978-3-030-78609-0_16 [Google Scholar]
13. Li, Yen-Hui Audrey
    1992 Indefinite wh in Mandarin Chinese. Journal of East Asian Linguistics.:–. 10.1007/BF00130234
    https://doi.org/10.1007/BF00130234 [Google Scholar]
14. Lin, Jo-Wang
    1996 Polarity Licensing and Wh-phrase Quantification in Chinese. Doctoral dissertation, University of Massachusetts at Amherst, Amherst, MA.
    [Google Scholar]
15. Lin, Jo-Wang
    1998 On existential polarity wh-phrases in Chinese. Journal of East Asian Linguistics.:–. 10.1023/A:1008284513325
    https://doi.org/10.1023/A:1008284513325 [Google Scholar]
16. Lu, Sin-En, Bo-Han Lu, Chao-Yi Lu, and Richard Tzong-Han Tsai
    2022 Exploring methods for building dialects-Mandarin code-mixing corpora: A case study in Taiwanese Hokkien. Findings of the Association for Computational Linguistics (EMNLP-2022), ed. byYoav Goldberg, Zornitsa Kozareva and Yue Zhang, –. Abu Dhabi, United Arab Emirates: Association for Computational Linguistics. 10.18653/v1/2022.findings‑emnlp.469
    https://doi.org/10.18653/v1/2022.findings-emnlp.469 [Google Scholar]
17. Nunan, David
    1993 Introducing Discourse Analysis. London: Penquin Group.
18. Pater, Joe
    2019 Generative linguistics and neural networks at 60: Foundation, friction, and fusion. Language.:–. 10.1353/lan.2019.0009
    https://doi.org/10.1353/lan.2019.0009 [Google Scholar]
19. Rajpurkar, Pranav, Jian Zhang, Konstantin Lopyrev, and Percy Liang
    2016 Squad: 100,000+ questions for machine comprehension of text. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-2016), ed. byJian Su, Kevin Duh and Xavier Carreras, –. Austin, TX: Association for Computational Linguistics. 10.18653/v1/D16‑1264
    https://doi.org/10.18653/v1/D16-1264 [Google Scholar]
20. Stowell, Tim
    1981 Origins of Phrase Structure. Doctoral dissertation, Massachusetts Institute of Technology, Cambridge, MA.
    [Google Scholar]
21. Sukthanker, Rhea, Poria Soujanya, Cambria Erik, and Thirunavukarasu Ramkumar
    2020 Anaphora and coreference resolution: A review. Information Fusion:–. 10.1016/j.inffus.2020.01.010
    https://doi.org/10.1016/j.inffus.2020.01.010 [Google Scholar]
22. Takahashi, Kosuke, Takahiro Omi, Kosuke Arima, and Tatsuya Ishigaki
    2023 Training Generative Question-answering on Synthetic Data Obtained from an Instruct-tuned Model. RetrievedSeptember 27, 2024, fromhttps://arxiv.org/abs/2310.08072
23. Tsai, Wei-Tien Dylan
    1994 On Economizing the Theory of A-Bar Dependencies. Doctoral dissertation, Massachusetts Institute of Technology, Cambridge, MA.
    [Google Scholar]
24. Wang, Wen-jet, Chia-jung Chen, Chia-ming Lee, Chien-yu Lai, and Hsin-hung Lin
    2019a Articut: Chinese Word Segmentation and POS Tagging System (Version 274) [Computer program]. RetrievedOctober 3, 2024fromhttps://api.droidtown.co
25. Wang, Wen-jet, Chia-jung Chen, Chia-ming Lee, Chien-yu Lai, and Hsin-hung Lin
    2019b Linguistics-Oriented Keyword Interface NLU System (Version 4.0) [Computer program]. RetrievedOctober 3, 2024fromhttps://api.droidtown.co
26. Wolfram, Stephen
    1985 Analytical and Empirical Mathematics with Computers (Report No. 8540). Princeton, NJ: The Institute for Advanced Study.
27. Zhou, Lexin, Wout Schellaert, Fernando Martínez-Plumed, Yael Moros-Daval, Cèsar Ferri, and José Hernández-Orallo
    2024 Larger and more instructable language models become less reliable. Nature:–. 10.1038/s41586‑024‑07930‑y
    https://doi.org/10.1038/s41586-024-07930-y [Google Scholar]
28. Zhu, Peide, Zhen Wang, Claudia Hauff, Jie Yang, and Avishek Anand
    2022 Answer quality aware aggregation for extractive QA crowdsourcing. Findings of the Association for Computational Linguistics (EMNLP 2022), ed. byYoav Goldberg, Zornitsa Kozareva and Yue Zhang, –. Stroudsburg, PA: The Association for Computational Linguistics. 10.18653/v1/2022.findings‑emnlp.457
    https://doi.org/10.18653/v1/2022.findings-emnlp.457 [Google Scholar]