| Large language models are implicitly topic models: Explaining and finding good demonstrations for in-context learning X Wang, W Zhu, M Saxon, M Steyvers, WY Wang arXiv preprint arXiv:2301.11916, 2023 | 37 | 2023 |
| Automatically correcting large language models: Surveying the landscape of diverse self-correction strategies L Pan, M Saxon, W Xu, D Nathani, X Wang, WY Wang arXiv preprint arXiv:2308.03188, 2023 | 20 | 2023 |
| End-to-End Spoken Language Understanding for Generalized Voice Assistants M Saxon, S Choudhary, JP McKenna, A Mouchtaris Interspeech 2021, 4738-4742, 2021 | 17 | 2021 |
| Objective measures of plosive nasalization in hypernasal speech M Saxon, J Liss, V Berisha ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 17 | 2019 |
| Say What? A Dataset for Exploring the Error Patterns That Two ASR Engines Make M Moore, M Saxon, H Venkateswara, V Berisha, S Panchanathan Proc. Interspeech 2019, 2528-2532, 2019 | 15 | 2019 |
| Investigating Memorization of Conspiracy Theories in Text Generation S Levy, M Saxon, WY Wang Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 …, 2021 | 12* | 2021 |
| Semantic Complexity in End-to-End Spoken Language Understanding JP McKenna, S Choudhary, M Saxon, GP Strimel, A Mouchtaris Proc. Interspeech 2020, 4273-4277, 2020 | 12 | 2020 |
| Robust Estimation of Hypernasality in Dysarthria with Acoustic Model Likelihood Features M Saxon, A Tripathi, Y Jiao, J Liss, V Berisha IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 2511-2522, 2020 | 11* | 2020 |
| Wikiwhy: Answering and explaining cause-and-effect questions M Ho, A Sharma, J Chang, M Saxon, S Levy, Y Lu, WY Wang arXiv preprint arXiv:2210.12152, 2022 | 7 | 2022 |
| Word pair convolutional model for happy moment classification M Saxon, S Bhandari, L Ruskin, G Honda Proceedings of the 2nd Workshop on Affective Content Analysis@ AAAI …, 2019 | 7 | 2019 |
| Not all errors are equal: Learning text generation metrics using stratified error synthesis W Xu, Y Tuan, Y Lu, M Saxon, L Li, WY Wang arXiv preprint arXiv:2210.05035, 2022 | 6 | 2022 |
| Self-supervised knowledge assimilation for expert-layman text style transfer W Xu, M Saxon, M Sra, WY Wang Proceedings of the AAAI Conference on Artificial Intelligence 36 (10), 11566 …, 2022 | 6 | 2022 |
| Causal balancing for domain generalization X Wang, M Saxon, J Li, H Zhang, K Zhang, WY Wang arXiv preprint arXiv:2206.05263, 2022 | 6 | 2022 |
| Multilingual Conceptual Coverage in Text-to-Image Models M Saxon, WY Wang | 4 | 2022 |
| Counterfactual maximum likelihood estimation for training deep networks X Wang, W Chen, M Saxon, WY Wang Advances in Neural Information Processing Systems 34, 25072-25085, 2021 | 4 | 2021 |
| Users are the North Star for AI Transparency A Mei, M Saxon, S Chang, ZC Lipton, WY Wang arXiv preprint arXiv:2303.05500, 2023 | 3 | 2023 |
| Modeling Disclosive Transparency in NLP Application Descriptions M Saxon, S Levy, X Wang, A Albalak, WY Wang arXiv preprint arXiv:2101.00433, 2021 | 3 | 2021 |
| PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers M Saxon, X Wang, W Xu, WY Wang arXiv preprint arXiv:2112.09237, 2021 | 2 | 2021 |
| UncommonVoice: A Crowdsourced Dataset of Dysphonic Speech M Moore, P Papreja, M Saxon, V Berisha, S Panchanathan Proc. Interspeech 2020, 2532-2536, 2020 | 2 | 2020 |
| Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning X Wang, W Zhu, M Saxon, M Steyvers, WY Wang Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 1 | 2023 |
William Yang WangMellichamp Chair Professor, University of California, Santa BarbaraVerified email at cs.ucsb.edu
