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Towards LLM-driven Automated Verification of Best Practices in Digital Public Infrastructures
Markovic, M., Sripada, S., Chakrabart, S. K., Diddigi, R. B.
Contributions to Conferences: Papers
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http://aura.abdn.ac.uk/bitstream/2164/24417/1/Markovic_etal_SICSA_Towards_LLM_Driven_AAM.pdf
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A Comparative Analysis of Metaphorical Cognition in ChatGPT and Human Minds
Mao, R., Chen, G., Li, X., Ge, M., Cambria, E.
Cognitive Computation
Contributions to Journals: Articles
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Do Language Models Exhibit Human-like Structural Priming Effects?
Jumelet, J., Zuidema, W., Sinclair, A.
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
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https://doi.org/10.18653/v1/2024.findings-acl.877
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http://aura.abdn.ac.uk/bitstream/2164/24554/1/Jumelet_etal_ACL62_Do_Language_Models_VOR.pdf
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View publication in Scopus
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Caregiver modelling and feedback in the context of early questions
Heim, J., Bala, M., Sinclair, A.
Contributions to Conferences: Papers
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http://aura.abdn.ac.uk/bitstream/2164/23919/2/CLS24_Heim_et_al_Caregiver_modelling_and_feedback.pdf
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Improving Factual Accuracy of Neural Table-to-Text Output by Addressing Input Problems in ToTTo
Sundararajan, B., Sripada, S., Reiter, E.
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
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https://aclanthology.org/2024.naacl-long.408.pdf
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Common Flaws in Running Human Evaluation Experiments in NLP
Thomson, C., Reiter, E., Belz, A.
Computational Linguistics, vol. 50, no. 2, pp. 795–805
Contributions to Journals: Articles
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https://doi.org/10.1162/coli_a_00508
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http://aura.abdn.ac.uk/bitstream/2164/23764/1/Thomson_etal_CL_Common_Flaws_in_VOR.pdf
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https://abdn.elsevierpure.com/en/publications/bdae6575-848e-4639-ae80-0a7f6dbe0f02
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Anchored Answers: Unravelling Positional Bias in GPT-2's Multiple-Choice Questions
Li, R., Gao, Y.
Working Papers and Discussion Papers
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file:///C:/Users/s01gv9/Downloads/2405.03205v2.pdf
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https://doi.org/10.48550/arXiv.2405.03205
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Listen Again and Choose the Right Answer: A New Paradigm for Automatic Speech Recognition with Large Language Models
Hu, Y., Chen, C., Qin, C., Zhu, Q., Chng, E. S., Li, R.
Working Papers and Discussion Papers
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https://doi.org/10.48550/arXiv.2405.10025
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Overcoming Catastrophic Forgetting by Exemplar Selection in Task-oriented Dialogue System
Chen, C., Li, R., Hu, Y., Chen, Y., Qin, C., Zhang, Q.
Working Papers and Discussion Papers
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file:///C:/Users/s01gv9/Downloads/2405.10992v1.pdf
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https://doi.org/10.48550/arXiv.2405.1099
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Large Language Models are Efficient Learners of Noise-Robust Speech Recognition
Hu, Y., Chen, C., Yang, C. H., Li, R., Zhang, C., Chen, P., Chng, E.
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
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file:///C:/Users/s01gv9/Downloads/4397_large_language_models_are_effi.pdf
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https://doi.org/10.48550/arXiv.2401.10446
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http://aura.abdn.ac.uk/bitstream/2164/22864/1/2401.10446v1.pdf