| ICL-D3IE: In-context learning with diverse demonstrations updating for document information extraction J He, L Wang, Y Hu, N Liu, H Liu, X Xu, HT Shen Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 17 | 2023 |
| Mitigating fine-grained hallucination by fine-tuning large vision-language models with caption rewrites L Wang, J He, S Li, N Liu, EP Lim International Conference on Multimedia Modeling, 32-45, 2024 | 11 | 2024 |
| T-sciq: Teaching multimodal chain-of-thought reasoning via large language model signals for science question answering L Wang, Y Hu, J He, X Xu, N Liu, H Liu, HT Shen Proceedings of the AAAI Conference on Artificial Intelligence 38 (17), 19162 …, 2024 | 9 | 2024 |
| MoCoSA: Momentum Contrast for Knowledge Graph Completion with Structure-Augmented Pre-trained Language Models J He, L Jia, L Wang, X Li, X Xu arXiv preprint arXiv:2308.08204, 2023 | 2 | 2023 |
| Alignment-enriched tuning for patch-level pre-trained document image models L Wang, J He, X Xu, N Liu, H Liu Proceedings of the AAAI Conference on Artificial Intelligence 37 (2), 2590-2598, 2023 | 1 | 2023 |
| Do-GOOD: Towards Distribution Shift Evaluation for Pre-Trained Visual Document Understanding Models J He, Y Hu, L Wang, X Xu, N Liu, H Liu, HT Shen Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | | 2023 |
| Do-GOOD: Towards distribution shift evaluation for pre-trained visual document understanding models.(2023) J HE, Y HU, L WANG, X XU, N LIU, H LIU SIGIR 23, 23-27, 0 | | |
