Hi there!
I am an Assistant Professor of Computer Science at Case Western Reserve University from Fall 2024. I completed my Ph.D. at Texas A&M University. My research focuses on machine learning, large language models (LLMs). You can contact me via xhan (at) case.edu.
google scholar / / bluesky / github / cv
🔥 News
- 2025.05: New preprints on Speculative Thinking, SELF, and Longer Context, Deeper Thinking form my group are out!
- 2025.05: Two papers on 💯-LongBench and CausalRAG accepted by ACL2025 Findings!
- 2025.04: Invited to serve as an Area Chair for NeurIPS2025!
- 2025.02: New preprint on Thinking Preference Optimization is out!
- 2025.02: One paper on You Only Debias Once is accepted by CPAL 2025 (Proceedings Track) Oral!
- 2024.12: Technical report of NeuralPLexer3 for biomolecular complex structure prediction is out!
- 2024.11: Graph Convolution≈Mixup is selected as Oral Presentation at LoG2024 TMLR Track!
- 2024.08: One paper on Understanding Graph Convolution accepted by TMLR!
- 2024.08: Excited to join Case Western Reserve University as an assistant professor!
- 2024.07: I am excited to start my MLsys internship at Iambic Therapeutics
- 2024.06: LLM Maybe LongLM has been selected as Spotlight (3.5%) at ICML2024!
Selected Publications(Google Scholar)
| [arXiv] | Longer Context, Deeper Thinking: Uncovering the Role of Long-Context Ability in Reasoning |
| Wang Yang, Zirui Liu, Hongye Jin, Qingyu Yin, Vipin Chaudhary, Xiaotian Han | |
| arXiv, 2025 | |
| [arXiv] | SELF: Self-Extend the Context Length With Logistic Growth Function |
| Phat Thanh Dang, Saahil Thoppay, Wang Yang, Qifan Wang, Vipin Chaudhary, Xiaotian Han | |
| arXiv, 2025 | |
| [arXiv] | Speculative Thinking: Enhancing Small Model Reasoning with Large Model Guidance at Inference Time |
| Wang Yang, Xiang Yue, Vipin Chaudhary, Xiaotian Han | |
| arXiv, 2025 | |
| [arXiv] | Thinking Preference Optimization |
| Wang Yang, Hongye Jin, Jingfeng Yang, Vipin Chaudhary, Xiaotian Han | |
| arXiv, 2025 | |
| [arXiv] | NeuralPLexer3: Physio-Realistic Biomolecular Structure Prediction with Flow Models |
| Zhuoran Qiao*, Feizhi Ding*, Thomas Dresselhaus*, Mia A Rosenfeld*, Xiaotian Han*, Owen Howell, Aniketh Iyengar, Stephen Opalenski, Anders S Christensen, Sai Krishna Sirumalla, Frederick R Manby, Thomas F Miller III, Matthew Welborn | |
| arXiv, 2025 | |
| [ACL2025 Findings] | 💯-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability? |
| Wang Yang, Hongye Jin, Shaochen Zhong, Song Jiang, Qifan Wang, Vipin Chaudhary, Xiaotian Han | |
| arXiv, 2025 | |
| [CPAL2025] | You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-offs at Inference Time |
| Xiaotian Han, Tianlong Chen, Kaixiong Zhou, Zhimeng Jiang, Zhangyang Wang, Xia Hu | |
| The Conference on Parsimony and Learning (CPAL), 2025 | |
| CPAL2025 Oral (12 in total) | |
| [ICML2024] | LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning |
| Hongye Jin*, Xiaotian Han*, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu | |
| International Conference on Machine Learning (ICML), 2024 | |
| ICML2024 Spotlight (3.5%) | |
| [TMLR2024] | On the Equivalence of Graph Convolution and Mixup |
| Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu | |
| Transactions on Machine Learning Research (TMLR), 2024 | |
| [ICLR2024] | FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods |
| Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu | |
| International Conference on Learning Representations (ICLR), 2024 | |
| [TKDD2024] | Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond |
| Jingfeng Yang*, Hongye Jin*, Ruixiang Tang*, Xiaotian Han*, Qizhang Feng*, Haoming Jiang, Bing Yin, Xia Hu | |
| Transactions on Knowledge and Data Engineering (TKDD), 2024 | |
| [arXiv] | GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length |
| Xiaotian Han*, Hongye Jin*, Jingfeng Yang, Zhimeng Jiang, Chia-Yuan Chang, Xia Hu | |
| arXiv, 2023 | |
| [NeurIPS2023] | Chasing Fairness under Distribution Shift: a Model Weight Perturbation Approach |
| Zhimeng Jiang*, Xiaotian Han*, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu | |
| Neural Information Processing Systems (NeurIPS), 2023 | |
| [ICLR2023] | MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization |
| Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah | |
| International Conference on Learning Representations (ICLR), 2023 | |
| [TMLR2023] | Retiring DP: New Distribution-Level Metrics for Demographic Parity |
| Xiaotian Han*, Zhimeng Jiang*, Hongye Jin*, Zirui Liu, Na Zou, Qifan Wang, Xia Hu | |
| Transactions on Machine Learning Research (TMLR), 2023 | |
| [ICML2022] | G-Mixup: Graph Augmentation for Graph Classification |
| Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu | |
| International Conference on Machine Learning (ICML), 2022 | |
| ICML2022 Outstanding Paper Award | |
| [WWW2022] | Graph Representation Learning via Unsupervised Rate Reduction Maximization |
| Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu | |
| The Web Conference (WWW), 2022 | |
| [IJCAI2018] | Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks |
| Xiaotian Han, Chuan Shi, Senzhang Wang, Philip, S Yu, Li Song | |
| International Joint Conference on Artificial Intelligence (IJCAI), 2018 | |
Education
- Ph.D. in Computer Science, Texas A&M University, College Station, TXSep 2019 – Aug 2024
- M.S. in Computer Science, Beijing University of Posts and TelecommunicationsSep 2016 – June 2019
- B.S. in Information Engineering, Shandong UniversitySep 2011 – June 2015
Awards & Honors
- ICML2022 Outstanding Paper Award2022
- Jane Street Graduate Research Fellowship Award Honorable Mention2024
- Excellent Ph.D. Student Award (One Per Year), Department of CSE, Texas A&M University2023
- NeurIPS 2023 Scholar Award2023
- Grad School Research and Presentation Travel Award, Texas A&M University2023
- Best Paper Awards, ADMA20182018
- Travel Grant, Department of CSE, Texas A&M University2022, 2023
- Travel Award, ICML20222022
- Outstanding Reviewer Award, ICML20222022
- Best Reviewer Award, CCF Transactions on Pervasive Computing and Interaction2019
- National Graduate Scholarship, Beijing University of Posts and Telecommunications2018
Professional Experiences
Iambic Therapeutics, San Diego, CAJuly 2024 – Dec 2024
- ML System Intern, Working on efficient LLM, Triton Kernel Devolvement, Protein Language Model Inference
- Mentor: Zhuoran Qiao
Amazon, Palo Alto, CAMay 2023 – Aug 2023
- Applied Scientist Intern, Large Language Model Alignment
- Mentor: Jingfeng Yang
Meta, Menlo Park, CASept 2022 – April 2023
- Research Intern, Understanding graph neural networks
- Mentor: Qifan Wang
Snap Research, Seattle, WAMay 2022 – Aug 2022
- Research Intern, Efficient large-scale graph neural networks
- Mentor: Neil Shah
Professional Services
Area Chair: NeurIPS 2025
Program Committee/Reviewer: ICLR 2024; WSDM 2024; CIKM 2023; ICML 2022, 2023; NeurIPS 2022, 2023, 2025; AAAI 2021, 2022, 2023, 2024; IJCAI 2021, 2023; WWW 2023; EMNLP 2023; ICDM 2022; KDD 2023; TIST 2023; TMLR 2023; TKDE 2023; TNNLS 2023; Neurocomputing 2023; TCPI 2019
Session Chair: WWW 2023; ICML 2022