Liv G. d'Aliberti

Room 320C, the Messiest Cubical

Sherrerd Hall

Princeton, NJ, 08544

I am a Computer Science Ph.D. student at Princeton University, advised by Manoel Horta Ribeiro and affiliated with the Humans and Machines (HAM) Lab. My research focuses on making AI reasoning and decision-making reliable, interpretable, and empirically grounded at scale.

Prior to starting my Ph.D., I worked as a research scientist at Leidos in their CTO Office Artificial Intelligence & Machine Learning Accelerator. I earned my Master of Science in Applied Mathematics and Statistics in 2019.

I enjoy working with individuals who are passionate about their research and excited about the potential impacts of their efforts. I’m hopeful that technology built using the research that my colleagues and I develop will help make our world (and maybe other worlds) safer and better for humans.

I really like all cats and one dog, my wife’s cavapoo. When I’m offline, I’m usually hiking, backpacking, skiing, or exploring new places.

news

May 20, 2026	Preprint released: Behavior-Consistent Deep Reinforcement Learning.
Apr 06, 2026	Paper accepted to Findings of ACL: The Illusion of Insight in Reasoning Models.
Mar 26, 2026	Patent published: HOLOGRAPHIC GRAPH TRANSFORMER NETWORK (HGTN) SYSTEM AND METHOD.
Feb 05, 2026	WMW 2026 was great.
Jan 02, 2026	Preprint released: The Illusion of Insight in Reasoning Models.

selected publications

Behavior-Consistent Deep Reinforcement Learning

Marcel Hussing , Liv G. d’Aliberti , Claas Voelcker, and 2 more authors

arXiv preprint arXiv:2605.21214, 2026

Preprint

arXiv Post Bib

@article{hussing2026behaviorconsistentdeepreinforcementlearning,
  title = {Behavior-Consistent Deep Reinforcement Learning},
  author = {Hussing, Marcel and d'Aliberti, Liv G. and Voelcker, Claas and Eysenbach, Benjamin and Eaton, Eric},
  journal = {arXiv preprint arXiv:2605.21214},
  year = {2026},
  eprint = {2605.21214},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  url = {https://arxiv.org/abs/2605.21214},
  post = {https://x.com/livdaliberti/status/2057876641653670026},
  note = {Preprint},
}

The Illusion of Insight in Reasoning Models

Liv G. d’Aliberti and Manoel Horta Ribeiro

In ACL Findings, 2026

arXiv Post Bib Code

@inproceedings{daliberti2026illusioninsightreasoningmodels,
  title = {The Illusion of Insight in Reasoning Models},
  author = {d'Aliberti, Liv G. and Horta Ribeiro, Manoel},
  booktitle = {ACL Findings},
  year = {2026},
  eprint = {2601.00514},
  archiveprefix = {arXiv},
  primaryclass = {cs.AI},
  url = {https://arxiv.org/abs/2601.00514},
  post = {https://x.com/manoelribeiro/status/2008261102853857393},
}

Explainability for Unmanned Aerial Vehicle Control via Multi-Objective Reinforcement Learning

Christian A. Clark , Kevin M. Albarado , Joshua P. Wilson, and 3 more authors

In 2025 IEEE Aerospace Conference, 2025

DOI Paper Bib

@inproceedings{11068676,
  author = {Clark, Christian A. and Albarado, Kevin M. and Wilson, Joshua P. and Bernard, Cedric A. and Scott, Jackson D. and D'Aliberti, Liv},
  booktitle = {2025 IEEE Aerospace Conference},
  title = {Explainability for Unmanned Aerial Vehicle Control via Multi-Objective Reinforcement Learning},
  year = {2025},
  volume = {},
  number = {},
  pages = {1-15},
  keywords = {Training;Command and control systems;Visualization;Reinforcement learning;Production;Autonomous aerial vehicles;Robustness;Fuels;Standards;Optimization},
  doi = {10.1109/AERO63441.2025.11068676},
  paper = {https://ieeexplore.ieee.org/document/11068676},
}

Grounded-Retrieval Adversarial Imitation Loop: Integrating Language, Agent, and World Models

Liv G. d’Aliberti and Manoel Horta Ribeiro

In NeurIPS 2025 Workshop on Bridging Language, Agent, and World Models for Reasoning and Planning, 2025

Paper Code