发表论文

1.Zhou, W., Liu, F., Zheng, H., & Zhao, R. (2025). Mitigating data bias and ensuring reliable evaluation of AI models with shortcut hull learning. Nature Communications, 16(1), 5513.

2.Shi, Q., Liu, F., Li, H., Li, G., Shi, L., & Zhao, R. (2025). Hybrid neural networks for continual learning inspired by corticohippocampal circuits. Nature Communications, 16(1), 1272.

3.Lin, J., Liu, Z., You, Y., Wang, J., Zhang, W., & Zhao, R. (2025, February). WeiPipe: Weight Pipeline Parallelism for Communication-Effective Long-Context Large Model Training. In Proceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (pp. 225-238).

4.Yang, Q., Xu, M., Li, H., Du, Y., Feng, D., & Zhao, R. (2025). Efficient Routing Congestion Prediction in Chip Design: Integrating Netlist Structure and Design Specifications With Heterogeneous Graph Attention Networks. IEEE Journal of the Electron Devices Society.

5.Niu, T., Huang, H., Du, Y., Zhang, W., Shi, L., & Zhao, R. (2025). General Automatic Solution Generation for Social Problems. Machine Intelligence Research, 22(1), 145-159.

6.Meng, Y., Lin, Y., Wang, T., Chen, Y., Wang, L., & Zhao, R. (2025). Diffusion-Based Extreme High-speed Scenes Reconstruction with the Complementary Vision Sensor. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 5701-5710).

7.Du, Y., Niu, T., & Zhao, R. (2025). Mixture of prompts learning for vision-language models. Frontiers in Artificial Intelligence, 8, 1580973.

1.Liu, F., Zheng, H., Ma, S., Zhang, W., Liu, X., Chua, Y., Shi, L., & Zhao, R. (2024). Advancing brain-inspired computing with hybrid neural networks. National Science Review, nwae066.

2.Niu, T., Huang, H., Du, Y., Zhang, W., Shi, L., & Zhao, R. (2024). General automatic solution generation for social problems. Machine Intelligence Research.

3.Niu, T., Zhang, W., & Zhao, R. (2024). Solution-oriented agent-based models generation with verifier-assisted iterative in-context learning. Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024).

4.Yang, Z., Wang, T., Lin, Y., Chen, Y., Zeng, H., Pei, J., Wang, J., Liu, X., Zhou, Y., Zhang, J., Wang, X., Lv, X., Zhao, R., & Shi, L. (2024). A vision chip with complementary pathways for open-world sensing. Nature, 629(8014), 1027–1033.

5.Huang, H., He, L., Liu, F., Zhao, R., & Shi, L. (2024). Neural dynamics pruning for energy-efficient spiking neural networks. 2024 IEEE International Conference on Multimedia and Expo (ICME), 1–6. IEEE.

1.Zeng, H., & Zhao, R. (2023). Perceptually-guided Dual-mode Virtual Reality System For Motion-adaptive Display. IEEE Transactions on Visualization and Computer Graphics, 29(5), 2249-2257.

2.Li, L., Shi, L., & Zhao, R. (2023, May). A Vertical-Horizontal Integrated Neuro-Symbolic Framework Towards Artificial General Intelligence. In International Conference on Artificial General Intelligence (pp. 197-206). Cham: Springer Nature Switzerland.

3.Li, H., Xu, M., Pei, J., & Zhao, R. (2023, August). Efficient GCN Deployment with Spiking Property on Spatial-Temporal Neuromorphic Chips. In Proceedings of the 2023 International Conference on Neuromorphic Systems (pp. 1-8).

4.Zheng, H., Lin, H., & Zhao, R. GUST: combinatorial generalization by unsupervised grouping with neuronal coherence. Advances in Neural Information Processing Systems, 36.

5.Li, H., Ma, S., Wang, T., Zhang, W., Wang, G., Song, C., ... & Zhao, R. (2023). HASP: Hierarchical asynchronous parallelism for multi-NN tasks. IEEE Transactions on Computers.