| Explainable subgraph reasoning for forecasting on temporal knowledge graphs Z Han, P Chen, Y Ma, V Tresp International conference on learning representations, 2020 | 198* | 2020 |
| TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting H Sun, J Zhong, Y Ma, Z Han, K He Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 142 | 2021 |
| Learning neural ordinary equations for forecasting future links on temporal knowledge graphs Z Han, Z Ding, Y Ma, Y Gu, V Tresp Proceedings of the 2021 conference on empirical methods in natural language …, 2021 | 131* | 2021 |
| The graph hawkes network for reasoning on temporal knowledge graphs Z Han, J Jiang, Y Wang, Y Ma, V Tresp Proceeding of the 2nd Conference on Automated Knowledge Base Construction (2020), 2019 | 111* | 2019 |
| A systematic survey of prompt engineering on vision-language foundation models J Gu, Z Han, S Chen, A Beirami, B He, G Zhang, R Liao, Y Qin, V Tresp, ... arXiv preprint arXiv:2307.12980, 2023 | 99 | 2023 |
| DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion Z Han, P Chen, Y Ma, V Tresp Proceeding of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 90 | 2020 |
| Time-dependent entity embedding is not all you need: A re-evaluation of temporal knowledge graph completion models under a unified framework Z Han, G Zhang, Y Ma, V Tresp Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 20 | 2021 |
| Multi-hop open-domain question answering over structured and unstructured knowledge Y Feng, Z Han, M Sun, P Li Findings of the Association for Computational Linguistics: NAACL 2022, 151-156, 2022 | 19 | 2022 |
| A simple but powerful graph encoder for temporal knowledge graph completion Z Ding, Y Ma, B He, J Wu, Z Han, V Tresp Intelligent Systems Conference, 729-747, 2023 | 18 | 2023 |
| TempCaps: a capsule network-based embedding model for temporal knowledge graph completion G Fu, Z Meng, Z Han, Z Ding, Y Ma, M Schubert, V Tresp, R Wattenhofer Proceedings of the Sixth Workshop on Structured Prediction for NLP (SPNLP …, 2022 | 18 | 2022 |
| Few-Shot Inductive Learning on Temporal Knowledge Graphs using Concept-Aware Information Z Ding, J Wu, B He, Y Ma, Z Han, V Tresp Proceeding of the 4th Conference on Automated Knowledge Base Construction (2022), 2022 | 17 | 2022 |
| Agtgan: Unpaired image translation for photographic ancient character generation H Huang, D Yang, G Dai, Z Han, Y Wang, KM Lam, F Yang, S Huang, ... Proceedings of the 30th ACM international conference on multimedia, 5456-5467, 2022 | 16 | 2022 |
| ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations Z Han, R Liao, J Gu, Y Zhang, Z Ding, Y Gu, H Köppl, H Schütze, V Tresp Findings of the Association for Computational Linguistics: ACL 2023, 5433–5447, 2022 | 15* | 2022 |
| Benchmarking robustness of adaptation methods on pre-trained vision-language models S Chen, J Gu, Z Han, Y Ma, P Torr, V Tresp Advances in Neural Information Processing Systems 36, 2024 | 14 | 2024 |
| ForecastTKGQuestions: A Benchmark for Temporal Question Answering and Forecasting over Temporal Knowledge Graphs Z Ding, Z Li, R Qi, J Wu, B He, Y Ma, Z Meng, S Chen, R Liao, Z Han, ... International Semantic Web Conference, 541-560, 2023 | 11* | 2023 |
| Learning Meta-Representations of One-shot Relations for Temporal Knowledge Graph Link Prediction Z Ding, B He, J Wu, Y Ma, Z Han, V Tresp 2023 International Joint Conference on Neural Networks (IJCNN), 1-10, 2023 | 11 | 2023 |
| Stop reasoning! when multimodal llms with chain-of-thought reasoning meets adversarial images Z Wang, Z Han, S Chen, F Xue, Z Ding, X Xiao, V Tresp, P Torr, J Gu arXiv preprint arXiv:2402.14899, 2024 | 7 | 2024 |
| Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks? S Chen, Z Han, B He, Z Ding, W Yu, P Torr, V Tresp, J Gu arXiv preprint arXiv:2404.03411, 2024 | 6 | 2024 |
| Continuous Temporal Graph Networks for Event-Based Graph Data J Guo, Z Han, Z Su, J Li, V Tresp, Y Wang Proceedings of the 2nd Workshop on Deep Learning on Graphs for Natural …, 2022 | 6 | 2022 |
| Understanding and Improving In-Context Learning on Vision-language Models S Chen, Z Han, B He, M Buckley, P Torr, V Tresp, J Gu arXiv preprint arXiv:2311.18021 1 (2), 2023 | 5 | 2023 |
Volker TrespLudwig-Maximilians-Universität München (LMU Munich)Verified email at dbs.ifi.lmu.de
