| Neural bellman-ford networks: A general graph neural network framework for link prediction Z Zhu, Z Zhang, LP Xhonneux, J Tang Advances in Neural Information Processing Systems 34, 29476-29490, 2021 | 377 | 2021 |
| RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs M Qu, J Chen, LP Xhonneux, Y Bengio, J Tang ICLR 2021, 2020 | 225 | 2020 |
| Continuous graph neural networks LP Xhonneux, M Qu, J Tang International Conference on Machine Learning, 10432-10441, 2020 | 185 | 2020 |
| Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs M Qu, T Gao, LP Xhonneux, J Tang International Conference on Machine Learning, 7867-7876, 2020 | 139 | 2020 |
| TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery Z Zhu, C Shi, Z Zhang, S Liu, M Xu, X Yuan, Y Zhang, J Chen, H Cai, J Lu, ... arXiv preprint arXiv:2202.08320, 2022 | 86 | 2022 |
| Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression LP Xhonneux, O Knight, Å Lernmark, E Bonifacio, WA Hagopian, ... Science translational medicine 13 (587), eabd5666, 2021 | 42 | 2021 |
| A* net: A scalable path-based reasoning approach for knowledge graphs Z Zhu, X Yuan, M Galkin, S Xhonneux, M Zhang, M Gazeau, J Tang Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 38 | 2023 |
| Efficient adversarial training in llms with continuous attacks S Xhonneux, A Sordoni, S Günnemann, G Gidel, L Schwinn Advances in Neural Information Processing Systems 37, 1502-1530, 2025 | 34 | 2025 |
| Soft prompt threats: Attacking safety alignment and unlearning in open-source llms through the embedding space L Schwinn, D Dobre, S Xhonneux, G Gidel, S Günnemann Advances in Neural Information Processing Systems 37, 9086-9116, 2025 | 34 | 2025 |
| How to transfer algorithmic reasoning knowledge to learn new algorithms? LPAC Xhonneux, A Deac, P Velickovic, J Tang NeurIPS2021, 2021 | 32 | 2021 |
| In-Context Learning Can Re-learn Forbidden Tasks S Xhonneux, D Dobre, J Tang, G Gidel, D Sridhar arXiv preprint arXiv:2402.05723, 2024 | 7 | 2024 |
| Learning to Efficiently Propagate for Reasoning on Knowledge Graphs Z Zhu, X Yuan, LP Xhonneux, M Zhang, M Gazeau, J Tang arXiv preprint arXiv:2206.04798, 2022 | 6 | 2022 |
| Deep Equilibrium Models For Algorithmic Reasoning S Xhonneux, Y He, A Deac, J Tang, G Gidel The Third Blogpost Track at ICLR 2024, 2024 | 3 | 2024 |
| Path-based reasoning for biomedical knowledge graphs with BioPathNet Y Hu, S Oleshko, S Firmani, Z Zhu, H Cheng, M Ulmer, M Arnold, ... bioRxiv, 2024 | 1 | 2024 |
| LLM-Safety Evaluations Lack Robustness T Beyer, S Xhonneux, S Geisler, G Gidel, L Schwinn, S Günnemann arXiv preprint arXiv:2503.02574, 2025 | | 2025 |
| A generative approach to LLM harmfulness detection with special red flag tokens S Xhonneux, D Dobre, M Mohfakhami, L Schwinn, G Gidel arXiv preprint arXiv:2502.16366, 2025 | | 2025 |
| Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives L Schwinn, Y Scholten, T Wollschläger, S Xhonneux, S Casper, ... arXiv preprint arXiv:2502.11910, 2025 | | 2025 |
| Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models M Noukhovitch, S Huang, S Xhonneux, A Hosseini, R Agarwal, ... arXiv preprint arXiv:2410.18252, 2024 | | 2024 |
| BioPathNet: Enhancing Link Prediction in Biomedical Knowledge Graphs through Path Representation Learning Y Hu, S Oleshko, S Firmani, Z Zhu, H Cheng, M Ulmer, M Arnold, ... Research Square, rs. 3. rs-5057842, 2024 | | 2024 |
| In-Context Learning, Can It Break Safety? S Xhonneux, D Dobre, M Noukhovitch, J Tang, G Gidel, D Sridhar ICML 2024 Next Generation of AI Safety Workshop, 0 | | |
Jian Tang (唐建）Associate Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI ChairVerified email at hec.ca
