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 Advances in Neural Information Processing Systems 36, 2024 | 109* | 2024 |
Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies L Pan, M Saxon, W Xu, D Nathani, X Wang, WY Wang Transactions of the Association for Computational Linguistics 12, 484-506, 2024 | 95* | 2024 |
End-to-End Spoken Language Understanding for Generalized Voice Assistants M Saxon, S Choudhary, JP McKenna, A Mouchtaris Interspeech 2021, 4738-4742, 2021 | 23 | 2021 |
Causal Balancing for Domain Generalization X Wang, M Saxon, J Li, H Zhang, K Zhang, WY Wang The Eleventh International Conference on Learning Representations, https …, 2023 | 20 | 2023 |
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 | 18 | 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 | 16* | 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 | 14* | 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 | 13 | 2020 |
Visual chain of thought: Bridging logical gaps with multimodal infillings D Rose, V Himakunthala, A Ouyang, R He, A Mei, Y Lu, M Saxon, ... arXiv preprint arXiv:2305.02317, 2023 | 12* | 2023 |
Wikiwhy: Answering and explaining cause-and-effect questions M Ho, A Sharma, J Chang, M Saxon, S Levy, Y Lu, WY Wang The Eleventh International Conference on Learning Representations, 2023 | 12 | 2023 |
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 | 12* | 2020 |
Multilingual Conceptual Coverage in Text-to-Image Models M Saxon, WY Wang Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 9 | 2023 |
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 Findings of the Association for Computational Linguistics: EMNLP 2022, 6559–6574, 2022 | 9 | 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 | 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 |
Users are the north star for AI transparency A Mei, M Saxon, S Chang, ZC Lipton, WY Wang arXiv preprint arXiv:2303.05500, 2023 | 6 | 2023 |
UncommonVoice: A Crowdsourced Dataset of Dysphonic Speech M Moore, P Papreja, M Saxon, V Berisha, S Panchanathan Proc. Interspeech 2020, 2532-2536, 2020 | 6 | 2020 |
Let’s think frame by frame with VIP: A video infilling and prediction dataset for evaluating video chain-of-thought V Himakunthala, A Ouyang, D Rose, R He, A Mei, Y Lu, C Sonar, ... Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 5* | 2023 |
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 Proceedings of the 17th Conference of the European Chapter of the …, 2023 | 5 | 2023 |
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 |