| Baichuan 2: Open large-scale language models A Yang, B Xiao, B Wang, B Zhang, C Bian, C Yin, C Lv, D Pan, D Wang, ... arXiv preprint arXiv:2309.10305, 2023 | 338* | 2023 |
| Inner attention based recurrent neural networks for answer selection B Wang, K Liu, J Zhao Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016 | 232 | 2016 |
| Tasty burgers, soggy fries: Probing aspect robustness in aspect-based sentiment analysis X Xing, Z Jin, D Jin, B Wang, Q Zhang, X Huang arXiv preprint arXiv:2009.07964, 2020 | 56 | 2020 |
| Conditional Generative Adversarial Networks for Commonsense Machine Comprehension. B Wang, K Liu, J Zhao IJCAI, 4123-4129, 2017 | 44 | 2017 |
| Neural question generation with answer pivot B Wang, X Wang, T Tao, Q Zhang, J Xu Proceedings of the AAAI conference on artificial intelligence 34 (05), 9138-9145, 2020 | 35 | 2020 |
| Shortgpt: Layers in large language models are more redundant than you expect X Men, M Xu, Q Zhang, B Wang, H Lin, Y Lu, X Han, W Chen arXiv preprint arXiv:2403.03853, 2024 | 33 | 2024 |
| T2ranking: A large-scale chinese benchmark for passage ranking X Xie, Q Dong, B Wang, F Lv, T Yao, W Gan, Z Wu, X Li, H Li, Y Liu, J Ma Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 32 | 2023 |
| Reco: A large scale chinese reading comprehension dataset on opinion B Wang, T Yao, Q Zhang, J Xu, X Wang Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 9146-9153, 2020 | 25 | 2020 |
| Employing External Rich Knowledge for Machine Comprehension. B Wang, S Guo, K Liu, S He, J Zhao IJCAI, 2929-2925, 2016 | 18 | 2016 |
| Document gated reader for open-domain question answering B Wang, T Yao, Q Zhang, J Xu, Z Tian, K Liu, J Zhao Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 16 | 2019 |
| Synthesis of a pomegranate shaped reduced graphene oxide stabilized secondary Si nanoparticles composite anode for lithium ion batteries X Men, X Kong, X Yang, B Wang, Y Wang, Y Liu, L Yu, H Li, B Xu International Journal of Hydrogen Energy 45 (53), 29492-29504, 2020 | 13 | 2020 |
| Cycle or Minkowski: which is more appropriate for knowledge graph embedding? H Yang, L Zhang, B Wang, T Yao, J Liu Proceedings of the 30th ACM International Conference on Information …, 2021 | 7 | 2021 |
| ComQA: Compositional question answering via hierarchical graph neural networks B Wang, T Yao, W Chen, J Xu, X Wang Proceedings of the Web Conference 2021, 2601-2612, 2021 | 7 | 2021 |
| SenSeNet: Neural keyphrase generation with document structure Y Luo, Z Li, B Wang, X Xing, Q Zhang, X Huang arXiv preprint arXiv:2012.06754, 2020 | 7 | 2020 |
| Deep semantic hashing with multi-adversarial training B Wang, K Liu, J Zhao Proceedings of the 27th ACM International Conference on Information and …, 2018 | 6 | 2018 |
| Chiqa: A large scale image-based real-world question answering dataset for multi-modal understanding B Wang, F Lv, T Yao, J Ma, Y Luo, H Liang Proceedings of the 31st ACM International Conference on Information …, 2022 | 3 | 2022 |
| Multi-lingual question generation with language agnostic language model B Wang, T Yao, W Chen, J Xu, X Wang Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 …, 2021 | 3 | 2021 |
| Exploring Context Window of Large Language Models via Decomposed Positional Vectors Z Dong, J Li, X Men, WX Zhao, B Wang, Z Tian, W Chen, JR Wen arXiv preprint arXiv:2405.18009, 2024 | 2 | 2024 |
| Base of RoPE Bounds Context Length X Men, M Xu, B Wang, Q Zhang, H Lin, X Han, W Chen arXiv preprint arXiv:2405.14591, 2024 | 2 | 2024 |
| Bridging the Gap Between Training and Inference of Bayesian Controllable Language Models H Liu, B Wang, T Yao, H Liang, J Xu, X Hu arXiv preprint arXiv:2206.05519, 2022 | 2 | 2022 |
Shangmin GuoUniversity of EdinburghVerified email at ed.ac.uk
