[EMNLP 2025, findings] Judging with Many Minds: Do More Perspectives Mean Less Prejudice? Chiyu Ma*, Enpei Zhang*, Yilun Zhao, Wenjun Liu, Yaning Jia, Peijun Qing, Lin Shi, Arman Cohan, Yujun Yan, Soroush Vosoughi.
[EMNLP 2025, findings] GENUINE: Graph Enhanced Multi-level Uncertainty Estimation for Large Language Models. Tuo Wang, Adithya Kulkarni, Tyler Cody, Peter A. Beling, Yujun Yan, Dawei Zhou.
[ACL 2025, findings] Spectral Insights into Data-Oblivious Critical Layers in Large Language Models. Xuyuan Liu, Lei Hsiung, Yaoqing Yang, Yujun Yan.
[KDD 2025] Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective. Gaotang Li, Danai Koutra, Yujun Yan. Paper
[KDD 2025] Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks. Tuo Wang, Jian Kang, Yujun Yan, Adithya Kulkarni, Dawei Zhou.
[ICML 2025] MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-Text Decoding. Weikang Qiu, Zheng Huang, Haoyu Hu, Aosong Feng, Yujun Yan, Rex Ying. Paper
[NeurIPS 2024] Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks. Conference on Neural Information Processing Systems (main conference, 25.8%). Xuyuan Liu, Yinghao Cai, Qihui Yang, Yujun Yan. Paper Code
[NeurIPS 2024] Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification. Conference on Neural Information Processing Systems (main conference, 25.8%). Yihe Wang, Nan Huang, Taida Li, Yujun Yan, Xiang Zhang. Paper Code
[NeurIPS 2024] Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance. Conference on Neural Information Processing Systems (main conference, 25.8%). Haiquan Lu*, Xiaotian Liu*, Yefan Zhou*, Qunli Li*, , Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang. Paper Code
[CIKM 2024] GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs. Vipul Gupta, Xin Chen, Ruoyun Huang, Fanlong Meng, Wei Xu, Jianjun Chen, Yujun Yan. The 33rd ACM International Conference on Information and Knowledge Management (applied research paper track). Paper
[ICML 2024] EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs. Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou. Forty-first International Conference on Machine Learning (27.5%). Paper Code
[ICML 2024] Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning. Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan. Forty-first International Conference on Machine Learning (27.5%). Paper Code
[KDD 2023] Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Research track, 22.1%). Paper Code
[Invited Paper 2023] Heterophily and Graph Neural Networks: Past, Present, and Future. Jiong Zhu, Yujun Yan, Mark Heimann, Lingxiao Zhao, Leman Akoglu, Danai Koutra. IEEE Data Engineering Bulletin, June 2023. Paper
[ICDM 2022] Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks. Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra. The IEEE International Conference on Data Mining (20%). Paper Code
[TheWebconf 2022] Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, and Danai Koutra. The ACM Web Conference (17.7%). Paper Code
[IEEE Big Data 2021] Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models. Zhengming Zhang*, Yaoqing Yang*, Zhewei Yao, Yujun Yan, Joseph E. Gonzalez, Michael W. Mahoney. IEEE International Conference on Big Data (19.9%). Paper Code
[3DV' 2021] A Dataset-dispersion Perspective on Reconstruction versus Recognition in Single-view 3D Reconstruction Networks. Yefan Zhou, Yiru Shen, Yujun Yan, Chen Feng, Yaoqing Yang. International Conference on 3D Vision. Paper Code
[NeurIPS' 2020] Neural Execution Engines: Learning to Execute Subroutines. Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi. Conference on Neural Information Processing Systems (20.1%). Paper Code Video
[NeurIPS' 2020] Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra. Conference on Neural Information Processing Systems (20.1%). Paper Code Video
[KDD' 2019, ORAL] GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data. Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sripada and Danai Koutra. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Research track, 9.2%). Paper Code Video
[SDM' 2018] Fast Flow-based Random Walk with Restart in a Multi-query Setting. Yujun Yan, Mark Heimann, Di Jin, Danai Koutra. SIAM International Conference on Data Mining (23.2%) Paper Supplementary File Code
[ICLR 2025 & WWW 2025 & AAAI 2025 Spring Symposium Series] Towards Agentic AI for Science: Hypothesis Generation, Comprehension, Quantification, and Validation. Danai Koutra, Lifu Huang, Adithya Kulkarni, Temiloluwa Prioleau, Beatrice Wan Yuan Soh, Qingyun Wu, Yujun Yan, Yaoqing Yang, Dawei Zhou, James Zou (Alphabetical order). ICLR Link WWW_Link AAAI_Link
[KDD' 2024, Undergraduate Consortium] Evaluating the Structural Awareness of Large Language Models on Graphs: Can They Count Substructures? Ly Nguyen, Yujun Yan. Link
[NeurIPS' 2017, WiML Workshop] Fast, Distributed Graph Methods in a Multi-query Setting. Yujun Yan, Danai Koutra. Women in Machine Learning Workshop, Conference on Neural Information Processing Systems. Link
[U.S. Application No. 17/068,691] Subroutine Neural Networks. Yujun Yan, Milad Hashemi, Kevin Swersky. (Works done while at Google)