Hi there!

I am currently a 4th-year Ph.D. student in the Department of Computer Science and Engineering at Texas A&M University. I am working at the DATA Lab under the supervision of Prof. Xia (Ben) Hu.

I am actively seeking an internship position for 2024, available in Spring, Summer, and Fall. Please kindly contact me if there is a good fit.

My research interests lie in LLMs, the general area of machine learning.

News

• 2024.01: Our new paper about LLMs’ context window extention is now avaivale at Arxiv: LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning. We propose Self-Extend to elicit LLMs’ inherent long context ability without any fine-tuning. It significantly improve the long contextn performance of LLMs and even can beat many fine-tuning based long-context method!
• 2023.09: One paper accepted by NeurIPS2023.
• 2023.05: One paper accepted by TMLR, Retiring ∆DP!
• 2023.04: New preprint Survey on LLMs!

Publications

• LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning [PDF]
  • Hongye Jin^*, Xiaotian Hann^*, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu
  • Preprint, 2024
• Learning Alignment and Compactness in Collaborative Filtering
  • Huiyuan Chen, Vivian Lai, Hongye Jin, Zhimeng Jiang, Mahashweta Das, Xia Hu
  • WSDM2024
• Chasing Fairness under Distribution Shift: a Model Weight Perturbation Approach [PDF]
  • Zhimeng Jiang^*, Xiaotian Han^*, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu.
  • NeurIPS2023
• Retiring ∆DP: New Distribution-Level Metrics for Demographic Parity. [PDF]
  • Xiaotian Han^*, Zhimeng Jiang^*, Hongye Jin^*, Zirui Liu, Na Zou, Qifan Wang, Xia Hu
  • TMLR, 2023
• Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond [PDF] [Github]
  • Jingfeng Yang^*, Hongye Jin^*, Ruixiang Tang^*, Xiaotian Han^*, Qizhang Feng^*, Haoming Jiang, Bing Yin, Xia Hu
  • Preprint, 2023
• Exposing Model Theft: A Robust and Transferable Watermark for Thwarting Model Extraction Attacks
  • Ruixiang Tang, Hongye Jin, Mengnan Du, Curtis Wigington, Rajiv Jain, and Xia Hu
  • CIKM(short)
• Disentangled graph collaborative filtering [PDF]
  • Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, Tat-Seng Chua
  • SIGIR, 2020.
• Transferring Fairness under Distribution Shift without Sensitive Information
  • Hongye Jin, Fan Yang, Cecilia Tilli, Saumitra Mishra, Xia Hu
  • Under Review
• GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length [PDF]
  • Hongye Jin^*, Xiaotian Han^*, Jingfeng Yang, Zhimeng Jiang, Chia-Yuan Chang, Xia Hu
  • Preprint, 2023
• Towards Mitigating Dimensional Collapse of Representations in Collaborative Filtering
  • Huiyuan Chen, Vivian Lai, Zhimeng Jiang, Hongye Jin, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu and Hao Yang
  • Under Review
• Gradient Rewiring for Editable Graph Neural Network Training
  • Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, Xia Hu
  • Under Review

Internships

• Visa Research, Palo Alto, CA. Sept 2022 – Dec 2022
  • Research Intern
  • Out-of-distribution Generalization of Graph Neural Networks
  • Work with Huiyuan Chen, Hao Yang.
• Damo Academy, Alibaba, Beijing, China. Dec. 2020 - Feb. 2021
  • Research Intern
  • Weak/distant-supervised learning for NLP.

Educations

• Aug. 2020 - now, Ph.D. Student, Computer Science, Texas A&M University.
• Sept. 2015 - July. 2020, Bacheler Degree, Computer Science, Peking University.

Professional Acitivities

• Conference Reviewer: WWW’23, KDD’23, ICDM’22, NeurIPS’23, AAAI’24
• Journal Reviewer: ACM Transactions on Intelligent Systems and Technology

Last updated on Jan 02, 2024.