Haoteng Yin
Computer Science · Purdue University West Lafayette
Publications
25
Citations
137
Est. group size
—
Recurring co-author estimate
Active years
9
Publishing since 2017
Haoteng Yin's work focuses on graph representation learning, especially making graph neural networks more scalable and efficient for tasks like link prediction and subgraph analysis. Related threads include privacy-preserving machine learning on graphs and relational data, applying large language models to structured data tasks, and predictive modeling for entity behavior such as pedestrian trajectories. Note that the publication list also contains some unrelated titles on infrared imaging, which appear to be mismatched entries rather than part of this researcher's core body of work.
Publication output was sparse before 2022 but has grown and stabilized at roughly 5-6 papers per year from 2022 through 2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Infrared image optical machine thermal radiation noise removal based on surface fitting
2025
- Research on anti-jamming technology of weak target on sea surface based on infrared polarization imaging
2025
- How to Talk to Language Models: Serialization Strategies for Structured Entity Matching
2025
- Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
arXiv (Cornell University) · 2025
- Differentially Private Relational Learning with Entity-level Privacy Guarantees
arXiv (Cornell University) · 2025
- SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents
Proceedings of the AAAI Conference on Artificial Intelligence · 2024
- Learning Scalable Structural Representations for Link Prediction with Bloom Signatures
2024
- SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents
arXiv (Cornell University) · 2024
- Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
arXiv (Cornell University) · 2024
- Single-pixel imaging with TCAO and untrained neural network
2024
- SUREL+: Moving from Walks to Sets for Scalable Subgraph-Based Graph Representation Learning
Proceedings of the VLDB Endowment · 2023
- SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning
arXiv (Cornell University) · 2023
- OCTAL: Graph Representation Learning for LTL Model Checking
arXiv (Cornell University) · 2023
- On the Inherent Privacy Properties of Discrete Denoising Diffusion Models
arXiv (Cornell University) · 2023
- Learning Scalable Structural Representations for Link Prediction with Bloom Signatures
arXiv (Cornell University) · 2023
- arXiv (Cornell University)×15
- Proceedings of the VLDB Endowment×2
- Scientia Sinica Informationis×1
- Proceedings of the AAAI Conference on Artificial Intelligence×1
- Beatrice Bevilacqua
Computer Science · Purdue University West Lafayette
- Satyaki Sikdar
Computer Science · Indiana University
- Yuntian He
Computer Science · The Ohio State University
- Mohammad Al Hasan
Computer Science · Indiana University
- Saket Gurukar
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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