@article{kasneci2023chatgpt, title={ChatGPT for good? On opportunities and challenges of large language models for education}, author={Kasneci, Enkelejda and Se{\ss}ler, Kathrin and K{\"u}chemann, Stefan and Bannert, Maria and Dementieva, Daryna and Fischer, Frank and Gasser, Urs and Groh, Georg and G{\"u}nnemann, Stephan and H{\"u}llermeier, Eyke and others}, journal={Learning and individual differences}, volume={103}, pages={102274}, year={2023}, publisher={Elsevier} } @article{chang2024survey, title={A survey on evaluation of large language models}, author={Chang, Yupeng and Wang, Xu and Wang, Jindong and Wu, Yuan and Yang, Linyi and Zhu, Kaijie and Chen, Hao and Yi, Xiaoyuan and Wang, Cunxiang and Wang, Yidong and others}, journal={ACM Transactions on Intelligent Systems and Technology}, volume={15}, number={3}, pages={1--45}, year={2024}, publisher={ACM New York, NY} } @inproceedings{kirchenbauer2023watermark, title={A watermark for large language models}, author={Kirchenbauer, John and Geiping, Jonas and Wen, Yuxin and Katz, Jonathan and Miers, Ian and Goldstein, Tom}, booktitle={International Conference on Machine Learning}, pages={17061--17084}, year={2023}, organization={PMLR} } @article{zhao2023survey, title={A survey of large language models}, author={Zhao, Wayne Xin and Zhou, Kun and Li, Junyi and Tang, Tianyi and Wang, Xiaolei and Hou, Yupeng and Min, Yingqian and Zhang, Beichen and Zhang, Junjie and Dong, Zican and others}, journal={arXiv preprint arXiv:2303.18223}, year={2023} } @inproceedings{xu2022systematic, title={A systematic evaluation of large language models of code}, author={Xu, Frank F and Alon, Uri and Neubig, Graham and Hellendoorn, Vincent Josua}, booktitle={Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming}, pages={1--10}, year={2022} } @article{wei2022emergent, title={Emergent abilities of large language models}, author={Wei, Jason and Tay, Yi and Bommasani, Rishi and Raffel, Colin and Zoph, Barret and Borgeaud, Sebastian and Yogatama, Dani and Bosma, Maarten and Zhou, Denny and Metzler, Donald and others}, journal={arXiv preprint arXiv:2206.07682}, year={2022} } @article{devlin2018bert, title={Bert: Pre-training of deep bidirectional transformers for language understanding}, author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina}, journal={arXiv preprint arXiv:1810.04805}, year={2018} } @article{koroteev2021bert, title={BERT: a review of applications in natural language processing and understanding}, author={Koroteev, Mikhail V}, journal={arXiv preprint arXiv:2103.11943}, year={2021} } @article{hao2019visualizing, title={Visualizing and understanding the effectiveness of BERT}, author={Hao, Yaru and Dong, Li and Wei, Furu and Xu, Ke}, journal={arXiv preprint arXiv:1908.05620}, year={2019} } @article{lin2022survey, title={A survey of transformers}, author={Lin, Tianyang and Wang, Yuxin and Liu, Xiangyang and Qiu, Xipeng}, journal={AI open}, volume={3}, pages={111--132}, year={2022}, publisher={Elsevier} } @article{bengesi2024advancements, title={Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers.}, author={Bengesi, Staphord and El-Sayed, Hoda and Sarker, Md Kamruzzaman and Houkpati, Yao and Irungu, John and Oladunni, Timothy}, journal={IEEE Access}, year={2024}, publisher={IEEE} } @article{silver2016mastering, title={Mastering the game of Go with deep neural networks and tree search}, author={Silver, David and Huang, Aja and Maddison, Chris J and Guez, Arthur and Sifre, Laurent and Van Den Driessche, George and Schrittwieser, Julian and Antonoglou, Ioannis and Panneershelvam, Veda and Lanctot, Marc and others}, journal={nature}, volume={529}, number={7587}, pages={484--489}, year={2016}, publisher={Nature Publishing Group} } @article{anthony2017thinking, title={Thinking fast and slow with deep learning and tree search}, author={Anthony, Thomas and Tian, Zheng and Barber, David}, journal={Advances in neural information processing systems}, volume={30}, year={2017} } @article{silver2017mastering, title={Mastering the game of go without human knowledge}, author={Silver, David and Schrittwieser, Julian and Simonyan, Karen and Antonoglou, Ioannis and Huang, Aja and Guez, Arthur and Hubert, Thomas and Baker, Lucas and Lai, Matthew and Bolton, Adrian and others}, journal={nature}, volume={550}, number={7676}, pages={354--359}, year={2017}, publisher={Nature Publishing Group} } @article{vaswani2017attention, title={Attention is all you need}, author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia}, journal={Advances in neural information processing systems}, volume={30}, year={2017} } @inproceedings{chaslot2008monte, title={Monte-carlo tree search: A new framework for game ai}, author={Chaslot, Guillaume and Bakkes, Sander and Szita, Istvan and Spronck, Pieter}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment}, volume={4}, number={1}, pages={216--217}, year={2008} } @article{gelly2011monte, title={Monte-Carlo tree search and rapid action value estimation in computer Go}, author={Gelly, Sylvain and Silver, David}, journal={Artificial Intelligence}, volume={175}, number={11}, pages={1856--1875}, year={2011}, publisher={Elsevier} } @article{gelly2012grand, title={The grand challenge of computer Go: Monte Carlo tree search and extensions}, author={Gelly, Sylvain and Kocsis, Levente and Schoenauer, Marc and Sebag, Michele and Silver, David and Szepesv{\'a}ri, Csaba and Teytaud, Olivier}, journal={Communications of the ACM}, volume={55}, number={3}, pages={106--113}, year={2012}, publisher={ACM New York, NY, USA} } @article{kaelbling1996reinforcement, title={Reinforcement learning: A survey}, author={Kaelbling, Leslie Pack and Littman, Michael L and Moore, Andrew W}, journal={Journal of artificial intelligence research}, volume={4}, pages={237--285}, year={1996} } @article{li2017deep, title={Deep reinforcement learning: An overview}, author={Li, Yuxi}, journal={arXiv preprint arXiv:1701.07274}, year={2017} } @article{franccois2018introduction, title={An introduction to deep reinforcement learning}, author={Fran{\c{c}}ois-Lavet, Vincent and Henderson, Peter and Islam, Riashat and Bellemare, Marc G and Pineau, Joelle and others}, journal={Foundations and Trends{\textregistered} in Machine Learning}, volume={11}, number={3-4}, pages={219--354}, year={2018}, publisher={Now Publishers, Inc.} } @inproceedings{henderson2018deep, title={Deep reinforcement learning that matters}, author={Henderson, Peter and Islam, Riashat and Bachman, Philip and Pineau, Joelle and Precup, Doina and Meger, David}, booktitle={Proceedings of the AAAI conference on artificial intelligence}, volume={32}, number={1}, year={2018} } @article{lecun2015deep, title={Deep learning}, author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey}, journal={nature}, volume={521}, number={7553}, pages={436--444}, year={2015}, publisher={Nature Publishing Group UK London} } @article{dulac2019challenges, title={Challenges of real-world reinforcement learning}, author={Dulac-Arnold, Gabriel and Mankowitz, Daniel and Hester, Todd}, journal={arXiv preprint arXiv:1904.12901}, year={2019} } @inproceedings{zhao2020sim, title={Sim-to-real transfer in deep reinforcement learning for robotics: a survey}, author={Zhao, Wenshuai and Queralta, Jorge Pe{\~n}a and Westerlund, Tomi}, booktitle={2020 IEEE symposium series on computational intelligence (SSCI)}, pages={737--744}, year={2020}, organization={IEEE} }