[20] Reinmar J Kobler, Jun ichiro Hirayama, Qibin Zhao, and Motoaki Kawanabe. SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022.
[21] Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7871-7880, 2020.
[22] Yi Li, Hualiang Wang, Yiqun Duan, and Xiaomeng Li. Clip surgery for better explainability with enhancement in open-vocabulary tasks. arXiv preprint arXiv:2304.05653, 2023.
[23] Yi Li, Hualiang Wang, Yiqun Duan, Hang Xu, and Xiaomeng Li. Exploring visual interpretability for contrastive language-image pre-training. arXiv preprint arXiv:2209.07046, 2022.
[24] Lun-De Liao, Chi-Yu Chen, I-Jan Wang, Sheng-Fu Chen, Shih-Yu Li, Bo-Wei Chen, Jyh-Yeong Chang, and Chin-Teng Lin. Gaming control using a wearable and wireless eeg-based brain-computer interface device with novel dry foam-based sensors. Journal of neuroengineering and rehabilitation, 9(1):1-12, 2012.
[25] Chin-Yew Lin. ROUGE: A package for automatic evaluation of summaries. In Text Summarization Branches Out, pages 74-81, Barcelona, Spain, July 2004. Association for Computational Linguistics.
[26] Joseph G Makin, David A Moses, and Edward F Chang. Machine translation of cortical activity to text with an encoder-decoder framework. Nature Neuroscience, 23(4):575-582, 2020.
[27] Dennis J McFarland, Charles W Anderson, K-R Muller, Alois Schlogl, and Dean J Krusienski. Bci meeting 2005-workshop on bci signal processing: feature extraction and translation. IEEE transactions on neural systems and rehabilitation engineering, 14(2):135-138, 2006.
[28] Anton Nijholt. Bci for games: A 'state of the art' survey. In Scott M. Stevens and Shirley J. Saldamarco, editors, Entertainment Computing - ICEC 2008, pages 225-228, 2009.
[29] Julie Onton, Marissa Westerfield, Jeanne Townsend, and Scott Makeig. Imaging human eeg dynamics using independent component analysis. *Neuroscience & biobehavioral reviews*, 30(6):808-822, 2006.
[30] Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems, 35:27730-27744, 2022.
[31] Yue-Ting Pan, Jing-Lun Chou, and Chun-Shu Wei. MAtt: A manifold attention network for EEG decoding. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022.
[32] Jerrin Thomas Panachakel, AG Ramakrishnan, and TV Ananthapadmanabha. A novel deep learning architecture for decoding imagined speech from eeg. arXiv preprint arXiv:2003.09374, 2020.
[33] Jerrin Thomas Panachakel and Angarai Ganesan Ramakrishnan. Decoding covert speech from eeg-a comprehensive review. Frontiers in Neuroscience, 15:392, 2021.
[34] Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics, pages 311-318, 2002.
[35] Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. Learning transferable visual models from natural language supervision. arXiv preprint arXiv:2103.00020, 2021.
[36] Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. Language models are unsupervised multitask learners. OpenAI blog, 1(8):9, 2019.
[37] Jaime F Delgado Saa and Mûjdat Çetin. Discriminative methods for classification of asynchronous imaginary motor tasks from eeg data. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 21(5):716-724, 2013.
[38] David Sabbagh, Pierre Ablin, Gael Varoquaux, Alexandre Gramfort, and Denis A. Engemann. Manifold-regression to predict from meg/egg brain signals without source modeling. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 32. Curran Associates, Inc., 2019.
[39] Pramit Saha, Muhammad Abdul-Mageed, and Sidney Fels. Speak your mind! towards imagined speech recognition with hierarchical deep learning. arXiv preprint arXiv:1904.05746, 2019.
[40] Simanto Saha and Mathias Baumert. Intra-and inter-subject variability in eeg-based sensorimotor brain computer interface: a review. Frontiers in computational neuroscience, 13:87, 2020.