1. Carl Allen and Timothy Hospedales . 2019 . Analogies Explained: Towards Understanding Word Embeddings . In Proceedings of the 36th International Conference on Machine Learning (Proceedings of Machine Learning Research , Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, Long Beach, CA, USA, 223-- 231 . https://proceedings.mlr.press/v97/allen19a.html Carl Allen and Timothy Hospedales. 2019. Analogies Explained: Towards Understanding Word Embeddings. In Proceedings of the 36th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, Long Beach, CA, USA, 223--231. https://proceedings.mlr.press/v97/allen19a.html
2. A causal framework for explaining the predictions of black-box
sequence-to-sequence models
3. Hangbo Bao , Li Dong , Furu Wei , Wenhui Wang , Nan Yang , Xiaodong Liu , Yu Wang , Jianfeng Gao , Songhao Piao , Ming Zhou , and Hsiao-Wuen Hon . 2020 . UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre- Training . In Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research , Vol. 119), Hal Daumé III and Aarti Singh (Eds.). PMLR, Vienna, Austria, 642--652. https://proceedings.mlr.press/v119/bao20a.html Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, and Hsiao-Wuen Hon. 2020. UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre- Training. In Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 119), Hal Daumé III and Aarti Singh (Eds.). PMLR, Vienna, Austria, 642--652. https://proceedings.mlr.press/v119/bao20a.html
4. Tom Brown , Benjamin Mann , Nick Ryder , Melanie Subbiah , Jared D Kaplan , Prafulla Dhariwal , Arvind Neelakantan , Pranav Shyam , Girish Sastry , Amanda Askell , Sandhini Agarwal , Ariel Herbert-Voss , Gretchen Krueger , Tom Henighan , Rewon Child , Aditya Ramesh , Daniel Ziegler , Jeffrey Wu , Clemens Winter , Chris Hesse , Mark Chen , Eric Sigler , Mateusz Litwin , Scott Gray , Benjamin Chess , Jack Clark , Christopher Berner , Sam McCandlish , Alec Radford , Ilya Sutskever , and Dario Amodei . 2020 . Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H . Lin (Eds.) , Vol. 33 . Curran Associates, Inc., virtual conference , 1877--1901. https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., virtual conference, 1877--1901. https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf
5. DISCO: Distilling Counterfactuals with Large Language Models