| Excar: Event graph knowledge enhanced explainable causal reasoning L Du, X Ding, K Xiong, T Liu, B Qin Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 24 | 2021 |
| Learning event graph knowledge for abductive reasoning L Du, X Ding, T Liu, B Qin Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 21 | 2021 |
| Folate intake and the risk of endometrial cancer: A meta-analysis L Du, Y Wang, H Zhang, H Zhang, Y Gao Oncotarget 7 (51), 85176, 2016 | 19 | 2016 |
| e-CARE: a new dataset for exploring explainable causal reasoning L Du, X Ding, K Xiong, T Liu, B Qin arXiv preprint arXiv:2205.05849, 2022 | 18 | 2022 |
| Modeling event background for if-then commonsense reasoning using context-aware variational autoencoder L Du, X Ding, T Liu, Z Li arXiv preprint arXiv:1909.08824, 2019 | 16 | 2019 |
| Cogbert: Cognition-guided pre-trained language models X Ding, B Chen, L Du, B Qin, T Liu Proceedings of the 29th International Conference on Computational …, 2022 | 10 | 2022 |
| Flm-101b: An open llm and how to train it with $100 k budget X Li, Y Yao, X Jiang, X Fang, X Meng, S Fan, P Han, J Li, L Du, B Qin, ... arXiv preprint arXiv:2309.03852, 2023 | 9 | 2023 |
| Mitigating reporting bias in semi-supervised temporal commonsense inference with probabilistic soft logic B Cai, X Ding, B Chen, L Du, T Liu Proceedings of the AAAI Conference on Artificial Intelligence 36 (10), 10454 …, 2022 | 9 | 2022 |
| multiDE: a dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data with multiple treatment conditions G Kang, L Du, H Zhang BMC bioinformatics 17, 1-16, 2016 | 9 | 2016 |
| Neural natural logic inference for interpretable question answering J Shi, X Ding, L Du, T Liu, B Qin Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 8 | 2021 |
| Quantifying and attributing the hallucination of large language models via association analysis L Du, Y Wang, X Xing, Y Ya, X Li, X Jiang, X Fang arXiv preprint arXiv:2309.05217, 2023 | 7 | 2023 |
| Heterogeneous graph knowledge enhanced stock market prediction K Xiong, X Ding, L Du, T Liu, B Qin AI Open 2, 168-174, 2021 | 7 | 2021 |
| Enhancing pretrained language models with structured commonsense knowledge for textual inference L Du, X Ding, K Xiong, T Liu, B Qin Knowledge-Based Systems 254, 109488, 2022 | 6 | 2022 |
| Discrimloss: A universal loss for hard samples and incorrect samples discrimination T Wu, X Ding, H Zhang, J Gao, M Tang, L Du, B Qin, T Liu IEEE Transactions on Multimedia, 2023 | 5 | 2023 |
| A graph enhanced bert model for event prediction L Du, X Ding, Y Zhang, K Xiong, T Liu, B Qin arXiv preprint arXiv:2205.10822, 2022 | 5 | 2022 |
| ReCo: Reliable causal chain reasoning via structural causal recurrent neural networks K Xiong, X Ding, Z Li, L Du, B Qin, Y Zheng, B Huai arXiv preprint arXiv:2212.08322, 2022 | 3 | 2022 |
| Towards Generalizable and Faithful Logic Reasoning over Natural Language via Resolution Refutation Z Sun, X Ding, L Du, B Cai, J Gao, T Liu, Q Bing arXiv preprint arXiv:2404.01677, 2024 | | 2024 |
| BiPFT: Binary Pre-trained Foundation Transformer with Low-rank Estimation of Binarization Residual Polynomials X Xing, L Du, X Wang, X Zeng, Y Wang, Z Zhang, J Zhang Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 16094 …, 2024 | | 2024 |
| Deciphering the lmpact of Pretraining Data on Large Language Models through Machine Unlearning Y Zhao, L Du, X Ding, K Xiong, Z Sun, J Shi, T Liu, B Qin arXiv preprint arXiv:2402.11537, 2024 | | 2024 |
| Text Difficulty Study: Do machines behave the same as humans regarding text difficulty? B Chen, X Ding, Y Zhao, B Fu, T Lin, B Qin, T Liu Machine Intelligence Research, 1-11, 2024 | | 2024 |
Xiao DingHarbin Institute of TechnologyVerified email at ir.hit.edu.cn
