In his dissertation, Haosen Ge, Ph.D. advances a novel theory that explains how low asset mobility helps foreign firms obtain preferential government treatment. #PSJMInfo

.Haosen Ge, Ph.D. is a PhD candidate at Princeton University whose research seeks to understand how foreign firms leverage political dynamics in host countries to influence policy outcomes.

In our new work - Algorithm Distillation - we show that transformers can improve themselves autonomously through trial and error without ever updating their weights. No prompting, no finetuning. A single transformer collects its own data and maximizes rewards on new tasks. 1/N

Given a trained #ML model, can we estimate how well it works on new data w/o seeing any labels? Can we still do it even if both covariates and labels shift in data? Our #NeurIPS2022 paper shows how to est model perf on new data in this hard case! arxiv.org/pdf/2209.08436… 1/2

Nothing to see here. Just an AI system learning to strategically plan world conquest, negotiate with humans in English and then betray them via the game of Diplomacy. science.org/doi/10.1126/sc…

An extremely fulfilling experience. A huge thanks to mentors @ Princeton Research Computing! researchcomputing.princeton.edu/news/2022/prin…

The winning moment ~ #Oliveira wins #IEM Katowice and is your 2023 StarCraft World Champion! #IEM #ESLProTour

Deadline in 2 days, send us your extended abstracts!!

It's been an incredible experience to present in this fantastic event! I've learned a lot from the brilliant work of others!

If you play chess, consider signing up for the study 😊🙏

Excited to present my work with Hamsa Bastani and Osbert Bastani at the Simons Institute for the Theory of Computing (Simons Institute for the Theory of Computing) ! We delve into the challenges with algorithmic fairness when dealing with human decision makers who can selectively comply.

Excited to see Philip K.H. Wong Centre The University of Hong Kong for promoting my working paper! I examined how Open Government Information mobilizes legal resistance in China but suffers a potenial backlash from local governments. Welcome any comments!

Thrilled to see that our paper made some waves! 🚀

Our paper is cited in Chapter 7 of the 2025 Economic Report of the President! whitehouse.gov/cea/written-ma…

Conformal prediction sets are a useful way to capture uncertainty for LLMs & deep learning models. But they're data-hungry! We propose a semi-bandit algo to learn these sets online. Check out our ICML Conference paper: arxiv.org/abs/2405.13268 Work led by Haosen Ge, Ph.D. & with Osbert Bastani