| Visual chatgpt: Talking, drawing and editing with visual foundation models C Wu, S Yin, W Qi, X Wang, Z Tang, N Duan arXiv preprint arXiv:2303.04671, 2023 | 486 | 2023 |
| Prophetnet: Predicting future n-gram for sequence-to-sequence pre-training W Qi, Y Yan, Y Gong, D Liu, N Duan, J Chen, R Zhang, M Zhou arXiv preprint arXiv:2001.04063, 2020 | 438 | 2020 |
| XGLUE: A new benchmark dataset for cross-lingual pre-training, understanding and generation Y Liang, N Duan, Y Gong, N Wu, F Guo, W Qi, M Gong, L Shou, D Jiang, ... arXiv preprint arXiv:2004.01401, 2020 | 283 | 2020 |
| CRADLE: cross-backend validation to detect and localize bugs in deep learning libraries HV Pham, T Lutellier, W Qi, L Tan 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019 | 137 | 2019 |
| Improving sign language translation with monolingual data by sign back-translation H Zhou, W Zhou, W Qi, J Pu, H Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 130 | 2021 |
| GLGE: A new general language generation evaluation benchmark D Liu, Y Yan, Y Gong, W Qi, H Zhang, J Jiao, W Chen, J Fu, L Shou, ... arXiv preprint arXiv:2011.11928, 2020 | 66 | 2020 |
| Prophetnet-x: Large-scale pre-training models for english, chinese, multi-lingual, dialog, and code generation W Qi, Y Gong, Y Yan, C Xu, B Yao, B Zhou, B Cheng, D Jiang, J Chen, ... arXiv preprint arXiv:2104.08006, 2021 | 57 | 2021 |
| DialogVED: A pre-trained latent variable encoder-decoder model for dialog response generation W Chen, Y Gong, S Wang, B Yao, W Qi, Z Wei, X Hu, B Zhou, Y Mao, ... arXiv preprint arXiv:2204.13031, 2022 | 41 | 2022 |
| Bang: Bridging autoregressive and non-autoregressive generation with large scale pretraining W Qi, Y Gong, J Jiao, Y Yan, W Chen, D Liu, K Tang, H Li, J Chen, ... International Conference on Machine Learning, 8630-8639, 2021 | 38 | 2021 |
| CRADLE: cross-backend validation to detect and localize bugs in deep learning libraries. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) HV Pham, T Lutellier, W Qi, L Tan IEEE, IEEE, Montreal, QC, Canada, 1027ś1038, 2019 | 35 | 2019 |
| Coderetriever: Unimodal and bimodal contrastive learning for code search X Li, Y Gong, Y Shen, X Qiu, H Zhang, B Yao, W Qi, D Jiang, W Chen, ... arXiv preprint arXiv:2201.10866, 2022 | 25 | 2022 |
| Conditional sentence generation and cross-modal reranking for sign language translation J Zhao, W Qi, W Zhou, N Duan, M Zhou, H Li IEEE Transactions on Multimedia 24, 2662-2672, 2021 | 24 | 2021 |
| Visual ChatGPT: Talking C Wu, S Yin, W Qi, X Wang, Z Tang, N Duan Drawing and Editing with Visual Foundation Models, 2023 | 17 | 2023 |
| Pos-constrained parallel decoding for non-autoregressive generation K Yang, W Lei, D Liu, W Qi, J Lv Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 16 | 2021 |
| CodeRetriever: A large scale contrastive pre-training method for code search X Li, Y Gong, Y Shen, X Qiu, H Zhang, B Yao, W Qi, D Jiang, W Chen, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 15 | 2022 |
| Metric-guided distillation: Distilling knowledge from the metric to ranker and retriever for generative commonsense reasoning X He, Y Gong, A Jin, W Qi, H Zhang, J Jiao, B Zhou, B Cheng, SM Yiu, ... arXiv preprint arXiv:2210.11708, 2022 | 14 | 2022 |
| Multi-level alignment pretraining for multi-lingual semantic parsing B Shao, Y Gong, W Qi, N Duan, X Lin Proceedings of the 28th International Conference on Computational …, 2020 | 9 | 2020 |
| Graph-based transformer with cross-candidate verification for semantic parsing B Shao, Y Gong, W Qi, G Cao, J Ji, X Lin Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8807-8814, 2020 | 9 | 2020 |
| Prophetnet-ads: A looking ahead strategy for generative retrieval models in sponsored search engine W Qi, Y Gong, Y Yan, J Jiao, B Shao, R Zhang, H Li, N Duan, M Zhou Natural Language Processing and Chinese Computing: 9th CCF International …, 2020 | 9 | 2020 |
| El-attention: Memory efficient lossless attention for generation Y Yan, J Chen, W Qi, N Bhendawade, Y Gong, N Duan, R Zhang International Conference on Machine Learning, 11648-11658, 2021 | 5 | 2021 |
Yu YanMicrosoft在 microsoft.com 的电子邮件经过验证
