I am currently a 4th year Ph.D. student at Texas A&M University, advised by Dr. Shuiwang Ji, who leads the Data Integration, Visualization, and Exploration (DIVE) Lab. Before TAMU, I obtained my bachelor’s degree in Electronic Engineering at Tsinghua University in July, 2021.
My research interest lies in deep learning, including (large) language model for science, trustworthy AI, graph DL analysis, out-of-distribution generalization, and causality. Currently, I am working on LLMs and their cross-combinations with geometric scientific tasks.
I am open to collaboration and actively seeking internship opportunities. If you're interested in working together or have opportunities available, please reach out to me!
Geometry Informed Tokenization of Molecules for Language Model Generation
Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji
arXiv preprint arXiv:2408.10120
Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models
Cong Fu*, Xiner Li*, Blake Olson, Heng Ji, Shuiwang Ji
arXiv preprint arXiv:2408.09730
Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding
Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gokcen Eraslan, Surag Nair, Tommaso Biancalani, Aviv Regev, Sergey Levine, Masatoshi Uehara
arXiv preprint arXiv:2408.08252
Eliminating Position Bias of Language Models: A Mechanistic Approach
Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M Kakade, Hao Peng, Heng Ji
arXiv preprint arXiv:2407.01100
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization
Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji
Forty-first International Conference on Machine Learning (ICML), 2024
TrustLLM: Trustworthiness in Large Language Models
Yue Huang*, Lichao Sun*, Haoran Wang*, Siyuan Wu*, Qihui Zhang*, Yuan Li*, Chujie Gao*, Yixin Huang*, Wenhan Lyu*, Yixuan Zhang*, Xiner Li*, Hanchi Sun*, Zhengliang Liu*, Yixin Liu*, Yijue Wang*, Zhikun Zhang*, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao
Forty-first International Conference on Machine Learning (ICML), 2024
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm
Shurui Gui*, Xiner Li*, Shuiwang Ji
The Twelfth International Conference on Learning Representations (ICLR), 2024
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
Neural Information Processing Systems (NeurIPS), 2023
Artificial intelligence for science in quantum, atomistic, and continuum systems
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, YuQing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K Joshi, Simon V Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji
arXiv preprint arXiv:2307.08423
GOOD: A Graph Out-of-Distribution Benchmark
Shurui Gui*, Xiner Li*, Limei Wang, Shuiwang Ji
Neural Information Processing Systems (NeurIPS), 2022 Datasets and Benchmarks Track
Keyword Search Based on Unsupervised Pre-Trained Acoustic Models
Xiner Li, Jing Zhao, Wei-Qiang Zhang, Zhiqiang Lv, Shen Huang
International Journal of Asian Language Processing, 2021
Dynamic 3D point cloud streaming: Distortion and concealment
Cheng-Hao Wu, Xiner Li, Rahul Rajesh, Wei Tsang Ooi, Cheng-Hsin Hsu
Network and Operating Systems Support for Digital Audio and Video (NOSSDAV), 2021
Workshop AI for New Drug Modalities at NeurIPS 2024
Conference on Neural Information Processing Systems (NeurIPS) 2023 - 2024
Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks track 2022 - 2024
International Conference on Machine Learning (ICML) 2023 - 2024
International Conference on Learning Representation (ICLR) 2024
AAAI Conference on Artificial Intelligence (AAAI) 2024
International Conference on Information and Knowledge Management (CIKM) 2023 - 2024
IEEE International Conference on Big Data (IEEE BigData) 2024
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)