Using Bayesian networks to discover relations between genes, environment, and disease C Su, A Andrew, MR Karagas, ME Borsuk BioData mining 6, 1-21, 2013 | 113 | 2013 |
Towards an ASR error robust Spoken Language Understanding System W Ruan, Y Nechaev, L Chen, C Su, I Kiss | 61 | 2020 |
ASR N-BEST FUSION NETS X Liu, M Li, L Chen, P Wanigasekara, W Ruan, H Khan, W Hamza, C Su, ... | 48 | 2021 |
A re-ranker scheme for integrating large scale nlu models C Su, R Gupta, S Ananthakrishnan, S Matsoukas 2018 IEEE Spoken Language Technology Workshop (SLT), 670-676, 2018 | 37 | 2018 |
Exploring transfer learning for end-to-end spoken language understanding S Rongali, B Liu, L Cai, K Arkoudas, C Su, W Hamza Proceedings of the AAAI Conference on Artificial Intelligence 35 (15), 13754 …, 2021 | 22 | 2021 |
Improving spoken language understanding by exploiting asr n-best hypotheses M Li, W Ruan, X Liu, L Soldaini, W Hamza, C Su arXiv preprint arXiv:2001.05284, 2020 | 22 | 2020 |
Improving structure mcmc for bayesian networks through markov blanket resampling C Su, ME Borsuk The Journal of Machine Learning Research 17 (1), 4042-4061, 2016 | 19 | 2016 |
Contextual natural language processing C Su, S Ananthakrishnan, S Matsoukas, S Saleem, R Gupta, K Ravikumar, ... US Patent 11,081,104, 2021 | 7 | 2021 |
Multi-task learning of spoken language understanding by integrating n-best hypotheses with hierarchical attention M Li, X Liu, W Ruan, L Soldaini, W Hamza, C Su Proceedings of the 28th International Conference on Computational …, 2020 | 7 | 2020 |
Incorporating prior expert knowledge in learning Bayesian networks from genetic epidemiological data C Su, ME Borsuk, A Andrew, M Karagas 2014 IEEE Conference on Computational Intelligence in Bioinformatics and …, 2014 | 7 | 2014 |
Overview of Bayesian network approaches to model gene-environment interactions and cancer susceptibility C Su, A Andrew, M Karagas, ME Borsuk | 7 | 2012 |
Semantic VL-BERT: Visual Grounding via Attribute Learning P Wanigasekara, K Qin, E Barut, F Yang, W Ruan, C Su | 4 | 2022 |
Multimodal Context Carryover P Wanigasekara, N Gupta, F Yang, E Barut, Z Raeesy, K Qin, S Rawls, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 3 | 2022 |
Natural language understanding processing C Su, S Matsoukas, S Ananthakrishnan, S Saleem, C Chan, Y Li, ... US Patent 11,335,346, 2022 | 3 | 2022 |
Introducing deep reinforcement learning to NLU ranking tasks G Yu, E Barut, C Su ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 2 | 2021 |
Optimizing NLU reranking using entity resolution signals in multi-domain dialog systems T Wang, J Chen, M Malmir, S Dong, X He, H Wang, C Su, Y Liu, Y Liu Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 2 | 2021 |
Speech processing B Liu, W Hamza, L Cai, K Arkoudas, C Su, S Rongali US Patent 11,682,400, 2023 | 1 | 2023 |
Contextual Domain Classification with Temporal Representations TH Lin, Y Shi, C Ye, F Yang, W Ruan, E Barut, W Hamza, C Su | 1 | 2021 |
Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought J Lee, F Yang, T Tran, Q Hu, E Barut, KW Chang, C Su arXiv preprint arXiv:2404.03414, 2024 | | 2024 |
Towards multi-modal co-reference resolution in conversational shopping agents S Osebe, P Wanigasekara, T Gueudre, T Tran, R Sharma, F Yang, Q Hu, ... | | 2024 |