| Qwen technical report J Bai, S Bai, Y Chu, Z Cui, K Dang, X Deng, Y Fan, W Ge, Y Han, F Huang, ... arXiv preprint arXiv:2309.16609, 2023 | 1475 | 2023 |
| A survey on in-context learning Q Dong, L Li, D Dai, C Zheng, J Ma, R Li, H Xia, J Xu, Z Wu, T Liu, ... arXiv preprint arXiv:2301.00234, 2022 | 1222 | 2022 |
| Qwen2 technical report A Yang, B Yang, B Hui, B Zheng, B Yu, C Zhou, C Li, C Li, D Liu, F Huang, ... arXiv preprint arXiv:2407.10671, 2024 | 532 | 2024 |
| Large language models are not fair evaluators P Wang, L Li, L Chen, Z Cai, D Zhu, B Lin, Y Cao, Q Liu, T Liu, Z Sui arXiv preprint arXiv:2305.17926, 2023 | 334 | 2023 |
| Table-to-text generation by structure-aware seq2seq learning T Liu, K Wang, L Sha, B Chang, Z Sui Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 306 | 2018 |
| Towards time-aware knowledge graph completion T Jiang, T Liu, T Ge, L Sha, B Chang, S Li, Z Sui Proceedings of COLING 2016, the 26th International Conference on …, 2016 | 186 | 2016 |
| A soft-label method for noise-tolerant distantly supervised relation extraction T Liu, K Wang, B Chang, Z Sui Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 163 | 2017 |
| Encoding temporal information for time-aware link prediction T Jiang, T Liu, T Ge, L Sha, S Li, B Chang, Z Sui Proceedings of the 2016 conference on empirical methods in natural language …, 2016 | 140 | 2016 |
| Order-planning neural text generation from structured data L Sha, L Mou, T Liu, P Poupart, S Li, B Chang, Z Sui Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 126 | 2018 |
| A token-level reference-free hallucination detection benchmark for free-form text generation T Liu, Y Zhang, C Brockett, Y Mao, Z Sui, W Chen, B Dolan arXiv preprint arXiv:2104.08704, 2021 | 118 | 2021 |
| Incorporating glosses into neural word sense disambiguation F Luo, T Liu, Q Xia, B Chang, Z Sui arXiv preprint arXiv:1805.08028, 2018 | 116 | 2018 |
| Document-level event extraction via heterogeneous graph-based interaction model with a tracker R Xu, T Liu, L Li, B Chang arXiv preprint arXiv:2105.14924, 2021 | 105 | 2021 |
| Enhancing topic-to-essay generation with external commonsense knowledge P Yang, L Li, F Luo, T Liu, X Sun Proceedings of the 57th annual meeting of the association for computational …, 2019 | 97 | 2019 |
| Leveraging gloss knowledge in neural word sense disambiguation by hierarchical co-attention F Luo, T Liu, Z He, Q Xia, Z Sui, B Chang Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 78 | 2018 |
| Learning to control the fine-grained sentiment for story ending generation F Luo, D Dai, P Yang, T Liu, B Chang, Z Sui, X Sun Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 64 | 2019 |
| Key fact as pivot: A two-stage model for low resource table-to-text generation S Ma, P Yang, T Liu, P Li, J Zhou, X Sun arXiv preprint arXiv:1908.03067, 2019 | 55 | 2019 |
| Unlocking efficiency in large language model inference: A comprehensive survey of speculative decoding H Xia, Z Yang, Q Dong, P Wang, Y Li, T Ge, T Liu, W Li, Z Sui arXiv preprint arXiv:2401.07851, 2024 | 53 | 2024 |
| Hierarchical encoder with auxiliary supervision for neural table-to-text generation: Learning better representation for tables T Liu, F Luo, Q Xia, S Ma, B Chang, Z Sui Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6786-6793, 2019 | 53 | 2019 |
| A two-stream AMR-enhanced model for document-level event argument extraction R Xu, P Wang, T Liu, S Zeng, B Chang, Z Sui arXiv preprint arXiv:2205.00241, 2022 | 51 | 2022 |
| Phrase-level self-attention networks for universal sentence encoding W Wu, H Wang, T Liu, S Ma Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 51 | 2018 |
Baobao CHANGPeking University在 pku.edu.cn 的电子邮件经过验证
