S. Gugger, L. Debut, T. Wolf, P. Schmid, Z. Mueller, S. Mangrulkar, M. Sun, and B. Bossan. Accelerate: Training and inference at scale made simple, efficient and adaptable, 2022. URL https://github.com/huggingface/accelerate.
S. Hochreiter and J. Schmidhuber. Long Short-Term Memory. Neural Computation, 9(8):1735-1780, Nov. 1997. ISSN 0899-7667. doi: 10.1162/neco.1997.9.8.1735. URL https://doi.org/10.1162/neco.1997.9.8.1735.
E. J. Hu, Y. Shen, P. Wallis, Z. Allen-Zhu, Y. Li, S. Wang, L. Wang, and W. Chen. LoRA: Low-Rank Adaptation of Large Language Models, Oct. 2021. URL http://arxiv.org/abs/2106.09685.arXiv:2106.09685 [cs].
J. D. Hunter. Matplotlib: A 2D Graphics Environment. Computing in Science & Engineering, 9(3): 90-95, May 2007. ISSN 1558-366X. doi: 10.1109/MCSE.2007.55. URL https://ieeexplore.ieee.org/document/4160265. Conference Name: Computing in Science & Engineering.
E. Jang, S. Gu, and B. Poole. Categorical Reparameterization with Gumbel-Softmax. In ICLR. arXiv, Aug. 2017. doi: 10.48550/arXiv.1611.01144. URL http://arxiv.org/abs/1611.01144.arXiv:1611.01144 [cs, stat].
N. Jaques, S. Gu, D. Bahdanau, J. M. Hernández-Lobato, R. E. Turner, and D. Eck. Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control. In International Conference on Machine Learning. arXiv, Oct. 2017. doi: 10.48550/arXiv.1611.02796. URL http://arxiv.org/abs/1611.02796. arXiv:1611.02796 [cs].
N. Jaques, A. Ghandeharioun, J. H. Shen, C. Ferguson, A. Lapedriza, N. Jones, S. Gu, and R. Picard. Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog, July 2019. URL http://arxiv.org/abs/1907.00456. arXiv:1907.00456 [cs, stat].
S. Kirby. Spontaneous evolution of linguistic structure—an iterated learning model of the emergence of regularity and irregularity. IEEE Transactions on Evolutionary Computation, 5(2):102-110, Apr. 2001. ISSN 1941-0026. doi: 10.1109/4235.918430. Conference Name: IEEE Transactions on Evolutionary Computation.
J. Kirkpatrick, R. Pascanu, N. Rabinowitz, J. Veness, G. Desjardins, A. A. Rusu, K. Milan, J. Quan, T. Ramalho, A. Grabska-Barwinska, D. Hassabis, C. Clopath, D. Kumaran, and R. Hadsell. Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences, 114(13):3521-3526, Mar. 2017. doi: 10.1073/pnas.1611835114. URL https://www.pnas.org/doi/10.1073/pnas.1611835114. Publisher: Proceedings of the National Academy of Sciences.
P. Koehn, H. Hoang, A. Birch, C. Callison-Burch, M. Federico, N. Bertoldi, B. Cowan, W. Shen, C. Moran, R. Zens, C. Dyer, O. Bojar, A. Constantin, and E. Herbst. Moses: Open Source Toolkit for Statistical Machine Translation. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions, pages 177-180, Prague, Czech Republic, June 2007. Association for Computational Linguistics. URL https://aclanthology.org/P07-2045.
N. Lambert, L. Tunstall, N. Rajani, and T. Thrush. HuggingFace H4 Stack Exchange Preference Dataset, 2023. URL https://huggingface.co/datasets/HuggingFaceH4/ stack-exchange/preferences.
A. Lazaridou and M. Baroni. Emergent Multi-Agent Communication in the Deep Learning Era, July 2020.
A. Lazaridou, A. Potapenko, and O. Tieleman. Multi-agent Communication meets Natural Language: Synergies between Functional and Structural Language Learning. In ACL. arXiv, May 2020. doi: 10.48550/arXiv.2005.07064. URL http://arxiv.org/abs/2005.07064. arXiv:2005.07064 [cs].
J. Lee, K. Cho, and D. Kiela. Countering Language Drift via Visual Grounding, Sept. 2019. URL http://arxiv.org/abs/1909.04499.arXiv:1909.04499 [cs].