| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 3439 | 2024 |
| Learning Combinatorial Optimization Algorithms over Graphs H Dai, EB Khalil, Y Zhang, B Dilkina, L Song Advances in Neural Information Processing Systems, 6348-6358, 2017 | 2276 | 2017 |
| Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261, 2025 | 1337 | 2025 |
| Adversarial attack on graph structured data H Dai, H Li, T Tian, X Huang, L Wang, J Zhu, L Song International conference on machine learning, 1115-1124, 2018 | 1089 | 2018 |
| Discriminative embeddings of latent variable models for structured data H Dai, B Dai, L Song International Conference on Machine Learning, 2702-2711, 2016 | 979 | 2016 |
| Recurrent Marked Temporal Point Processes: Embedding Event History to Vector N Du, H Dai, R Trivedi, U Upadhyay, M Gomez-Rodriguez, L Song Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 934 | 2016 |
| Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs R Trivedi, H Dai, Y Wang, L Song International Conference on Machine Learning, 3462-3471, 2017 | 741 | 2017 |
| Variational reasoning for question answering with knowledge graph Y Zhang, H Dai, Z Kozareva, AJ Smola, L Song Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 676 | 2018 |
| Syntax-Directed Variational Autoencoder for Structured Data H Dai, Y Tian, B Dai, S Skiena, L Song Proceedings of the International Conference on Learning Representations …, 2018 | 531* | 2018 |
| Sequential click prediction for sponsored search with recurrent neural networks Y Zhang, H Dai, C Xu, J Feng, T Wang, J Bian, B Wang, TY Liu Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014 | 434 | 2014 |
| Learning universal policies via text-guided video generation Y Du, S Yang, B Dai, H Dai, O Nachum, J Tenenbaum, D Schuurmans, ... Advances in Neural Information Processing Systems 36, 2024 | 392 | 2024 |
| Material structure-property linkages using three-dimensional convolutional neural networks A Cecen, H Dai, YC Yabansu, SR Kalidindi, L Song Acta Materialia 146, 76-84, 2018 | 383 | 2018 |
| Learning Steady-States of Iterative Algorithms over Graphs H Dai, Z Kozareva, B Dai, A Smola, L Song International Conference on Machine Learning, 1114-1122, 2018 | 329 | 2018 |
| Retrosynthesis prediction with conditional graph logic network H Dai, C Li, C Coley, B Dai, L Song Advances in Neural Information Processing Systems, 8872-8882, 2019 | 309 | 2019 |
| Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs E Dinella, H Dai, Z Li, M Naik, L Song, K Wang Proceedings of the International Conference on Learning Representations …, 2020 | 297 | 2020 |
| Deep Coevolutionary Network: Embedding User and Item Features for Recommendation H Dai, Y Wang, R Trivedi, L Song | 222* | 2017 |
| Learning loop invariants for program verification X Si, H Dai, M Raghothaman, M Naik, L Song Advances in Neural Information Processing Systems 31, 7751-7762, 2018 | 211 | 2018 |
| Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search B Chen, C Li, H Dai, L Song International Conference on Machine Learning, 1608-1616, 2020 | 202 | 2020 |
| CompILE: Compositional Imitation Learning and Execution T Kipf, Y Li, H Dai, V Zambaldi, A Sanchez-Gonzalez, E Grefenstette, ... International Conference on Machine Learning, 3418-3428, 2019 | 201 | 2019 |
| A probabilistic model for learning multi-prototype word embeddings F Tian, H Dai, J Bian, B Gao, R Zhang, E Chen, TY Liu Proceedings of COLING 2014, the 25th International Conference on …, 2014 | 196 | 2014 |
Le SongCTO, GenBio AI; Professor, MBZUAIVerified email at mbzuai.ac.ae
