Rohin Manvi

I am a CS PhD student at BAIR, advised by Sergey Levine. I am also a researcher at Liquid AI. Previously, I was a CS undergrad (and part coterm) at Stanford, where I had the opportunity to work with Stefano Ermon.

selected publications

Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation

Rohin Manvi, Anikait Singh, and Stefano Ermon

2024

arXiv Bib

@misc{manvi2024adaptiveinferencetimecomputellms,
  title = {Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation},
  author = {Manvi, Rohin and Singh, Anikait and Ermon, Stefano},
  year = {2024},
  eprint = {2410.02725},
  archiveprefix = {arXiv},
  primaryclass = {cs.CL},
  url = {https://arxiv.org/abs/2410.02725},
}

Large Language Models are Geographically Biased

Rohin Manvi, Samar Khanna, Marshall Burke, David B. Lobell, and Stefano Ermon

In Forty-first International Conference on Machine Learning, 2024

arXiv Bib Code

@inproceedings{manvi2024large,
  title = {Large Language Models are Geographically Biased},
  author = {Manvi, Rohin and Khanna, Samar and Burke, Marshall and Lobell, David B. and Ermon, Stefano},
  booktitle = {Forty-first International Conference on Machine Learning},
  year = {2024},
  url = {https://arxiv.org/abs/2402.02680},
  journal = {Forty-first International Conference on Machine Learning, 2024},
}

GeoLLM: Extracting Geospatial Knowledge from Large Language Models

Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David B. Lobell, and Stefano Ermon

In The Twelfth International Conference on Learning Representations, 2024

arXiv Bib Code Website

@inproceedings{manvi2024geollm,
  title = {Geo{LLM}: Extracting Geospatial Knowledge from Large Language Models},
  author = {Manvi, Rohin and Khanna, Samar and Mai, Gengchen and Burke, Marshall and Lobell, David B. and Ermon, Stefano},
  booktitle = {The Twelfth International Conference on Learning Representations},
  year = {2024},
  url = {https://arxiv.org/abs/2310.06213},
  journal = {The Twelfth International Conference on Learning Representations, 2024},
}