Publications

Conference

• Finding the Cracks: Improving LLMs Reasoning with Paraphrastic Probing and Consistency Verification (under review)
  Weili Shi, Dongliang Guo, Lehan Yang, Tianlong Wang, Hanzhang Yuan, Sheng Li.

• LLMs Are Too Smart to Be Average: Controlling LLM Proficiency via Guided Decoding (under review)
  Dongliang Guo, Weili Shi, Sheng Li.

• Revisiting Dynamic Graphs from the Perspective of Time Series (under review)
  Weili Shi, Dongliang Guo, Sheng Li.

• Leveraging Large Language Models for Dynamic Text-Attributed Graphs Learning (under review)
  Weili Shi, Haoming Li, Sheng Li.

• VRMDiff: TextGuided Video Referring Matting Generation of Diffusion (under review)
  Lehan Yang, Jincen Song, Tianlong Wang, Daiqing Qi, Weili Shi, Yuheng Liu, Sheng Li.

• ItinBench: Benchmarking Planning Across Multiple Cognitive Dimensions with Large Language Models (under review)
  Tianlong Wang, Weili Shi, Sheng Li.

• Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning
  Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023.
  Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, Sheng Li.

• Aging Contrast: A Contrastive Learning Framework for Fish Re-identification Across Seasons and Years
  Australasian Joint Conference on Artificial Intelligence (AJCAI), 2023.
  Weili Shi*, Zhongliang Zhou, Benjamin H. Letcher, Nathaniel Hitt, Yoichiro Kanno, Ryo Futamura,Osamu Kishida, Kentaro Morita, Sheng Li. ( denotes equal contribution)

• Pairwise adversarial training for unsupervised classimbalanced domain adaptation
  Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022.
  Weili Shi, Ronghang Zhu, Sheng Li.

• Improving Robustness of Vision Transformers via Data-Augmented Virtual Adversarial Training
  2022 IEEE International Conference on Big Data (IEEE Big Data), 2022
  Weili Shi, Sheng Li.

• Pigmentation-based Visual Learning for Salvelinus fontinalis Individual Re-identification
  2022 IEEE International Conference on Big Data (IEEE Big Data), 2022
  Zhou, Zhongliang, Nathaniel P. Hitt, Benjamin H. Letcher, Weili Shi, Sheng Li.

Journal

• Optimized Graph Structures for Calibrating Graph Neural Networks with Out-of-Distribution Nodes (under review)
  Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, Sheng Li.

• A survey of deep graph learning under distribution shifts: from graph out-of-distribution generalization to adaptation (under review)
  Kexin Zhang, Shuhan Liu, Song Wang, Weili Shi, Chen Chen, Pan Li, Sheng Li, Jundong Li, Kaize Ding.

• Dual-windowed Vision Transformer with Angular Self-Attention
  Transactions on Machine Learning Research (TMLR), 2024.
  Weili Shi, Sheng Li.

• Unsupervised Class-imbalanced Domain Adaptation with Pairwise Adversarial Training and Semantic Alignment
  IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2024.
  Weili Shi, Ronghang Zhu, Sheng Li.

• Improving Robustness of Vision Transformers via Data-Augmented Virtual Adversarial Training
  IEEE Transactions on Big Data (IEEE TBD), 2024.
  Weili Shi, Sheng Li.

• Application of artificial intelligence to the monitoring of medication adherence for tuberculosis treatment in Africa: algorithm development and validation
  ournal of Medical Internet Research AI (JMIR AI), 2023
  Juliet Sekandi, Weili Shi, Ronghang Zhu, Patrick Kaggwa, Ernest Mwebaze, Sheng Li.