Ye, H., He, X., Arak, V., Dong, H., & Song, G. (2026). Meta context engineering via agentic skill evolution. ICML 2026.

Dong, H., Jiang, K., Ye, H., Zhu, W., Kang, Z., & Song, G. (2026). NeuReasoner: Towards explainable, controllable, and unified reasoning via mixture-of-neurons. ACL 2026 Main (Oral).

Ye, H., Jin, J., Xie, Y., Zhang, X., & Song, G. (2025). Large language model psychometrics: A systematic review of evaluation, validation, and enhancement.

Ye, H., Zhang, T., Xie, Y., Zhang, L., Ren, Y., Zhang, X., & Song, G. (2025). Generative psycho-lexical approach for constructing value systems in large language models. ACL 2025 Main.

Ye, H., Xie, Y., Ren, Y., Fang, H., Zhang, X., & Song, G. (2025). Measuring human and AI values based on generative psychometrics with large language models. AAAI 2025.

Hou, Y., Ye, H., Yang, S., Zhang, Y., Xu, S., & Song, G. (2025). TransPlace: Transferable circuit global placement via graph neural network. KDD 2025.

Berto, F., Hua, C., Park, J., Luttmann, L., Ma, Y., Bu, F., Wang, J., Ye, H., Kim, M., et al. (2025). RL4CO: An extensive reinforcement learning for combinatorial optimization benchmark. KDD 2025 D&B Track.

Ren, Y., Ye, H., Fang, H., Zhang, X., & Song, G. (2024). ValueBench: Towards comprehensively evaluating value orientations and understanding of large language models. ACL 2024 Main.

Ye, H., Wang, J., Cao, Z., Berto, F., Hua, C., Kim, H., Park, J., & Song, G. (2024). ReEvo: Large language models as hyper-heuristics with reflective evolution. NeurIPS 2024.

Ye, H., Wang, J., Liang, H., Cao, Z., Li, Y., & Li, F. (2024). GLOP: Learning global partition and local construction for solving large-scale routing problems in real-time. AAAI 2024.

Hou, Y., Ye, H., Zhang, Y., Xu, S., & Song, G. (2024). RoutePlacer: An end-to-end routability-aware placer with graph neural network. KDD 2024.

Ye, H., Wang, J., Cao, Z., Liang, H., & Li, Y. (2023). DeepACO: Neural-enhanced ant systems for combinatorial optimization. NeurIPS 2023.