Justin Cui

Burnaby, Vancouver

I am a first-year MIIS student at the Language Technologies Institute in the School of Computer Science at Carnegie Mellon University. My research focuses on human-AI interaction.

I’m interested in building intelligent, fluid interfaces that augment human workflow rather than replace it—supporting complex and creative tasks through systems that enhance rather than automate human capabilities.

Currently, I’m working with Professor Tovi Grossman on LOOM, a proactive learning system that builds personalized knowledge graphs from user interactions. We are continuing to develop visualizations that help users see how concepts connect and identify gaps in their understanding.

Previously, I worked with Professor Scott Sanner on retrieval-augmented conversational recommendation (SIGIR 2024), grounding LLM recommendations in structured data and user reviews. I also explored score-based generative models with Professor Alán Aspuru-Guzik at the Vector Institute.

Reach out at justincu@andrew.cmu.edu!

selected publications

AAAI

LOOM: Personalized Learning Informed by Daily LLM Conversations Toward Long-Term Mastery via a Dynamic Learner Memory Graph

J. Cui, K. Pu, and T. Grossman

In PerFM @ AAAI, 2026

Bib PDF Code

@inproceedings{cui2026loom,
  title = {LOOM: Personalized Learning Informed by Daily LLM Conversations Toward Long-Term Mastery via a Dynamic Learner Memory Graph},
  author = {Cui, J. and Pu, K. and Grossman, T.},
  booktitle = {PerFM @ AAAI},
  year = {2026},
  url = {https://arxiv.org/abs/2511.21037},
}

SIGIR

Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking

S. Kemper^*, J. Cui^*, K. Dicarlantonio^*, K. Lin^*, D. Tang^*, A. Korikov, and S. Sanner

* denotes equal contribution

In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Bib PDF Code

@inproceedings{kemper2024retrieval,
  title = {Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking},
  author = {Kemper, S. and Cui, J. and Dicarlantonio, K. and Lin, K. and Tang, D. and Korikov, A. and Sanner, S.},
  booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year = {2024},
  url = {https://arxiv.org/pdf/2406.00033},
}

arXiv

A Simple but Effective Elaborative Query Reformulation Approach for Natural Language Recommendation

Q. Wen^*, Y. Liu^*, J. Cui^*, J. Zhang, A. Korikov, G. K. Saad, and S. Sanner

* denotes equal contribution

arXiv preprint arXiv:2510.02656, 2025

Bib PDF

@article{wen2025elaborative,
  title = {A Simple but Effective Elaborative Query Reformulation Approach for Natural Language Recommendation},
  author = {Wen, Q. and Liu, Y. and Cui, J. and Zhang, J. and Korikov, A. and Saad, G. K. and Sanner, S.},
  journal = {arXiv preprint arXiv:2510.02656},
  year = {2025},
  url = {https://arxiv.org/abs/2510.02656},
}