10 papers
Value Over Language Model: Detecting Original Contribution in Writing
Vibhhu Sharma, Thorsten Joachims, Sarah Dean
LLMs have been rapidly adopted across writing tasks, prompting the development of tools for detecting LLM-generated text. Yet, these tools largely measure how much of a document's…
Mind the Residual Gap: Probabilistic Downscaling under Real-World Bias
Yujin Kim, Nidhi Soma, Sarah Dean
Probabilistic downscaling models the conditional distribution of high-resolution fields given coarse inputs and is a core challenge in atmospheric science, climate modeling, and ot…
Do LLMs Favor LLMs? Quantifying Interaction Effects in Peer Review
Vibhhu Sharma, Thorsten Joachims, Sarah Dean
There are increasing indications that LLMs are not only used for producing scientific papers, but also as part of the peer review process. In this work, we provide the first compre…
Sparse-to-Field Reconstruction via Stochastic Neural Dynamic Mode Decomposition
Yujin Kim, Sarah Dean
Many consequential real-world systems, like wind fields and ocean currents, are dynamic and hard to model. Learning their governing dynamics remains a central challenge in scientif…
High-Altitude Balloon Station-Keeping with First Order Model Predictive Control
Myles Pasetsky, Jiawei Lin, Bradley Guo +1
High-altitude balloons (HABs) are common in scientific research due to their wide range of applications and low cost. Because of their nonlinear, underactuated dynamics and the par…
Pre-trained Large Language Models Learn Hidden Markov Models In-context
Yijia Dai, Zhaolin Gao, Yahya Sattar +2
Hidden Markov Models (HMMs) are foundational tools for modeling sequential data with latent Markovian structure, yet fitting them to real-world data remains computationally challen…
Policy Design for Two-sided Platforms with Participation Dynamics
Haruka Kiyohara, Fan Yao, Sarah Dean
In two-sided platforms (e.g., video streaming or e-commerce), viewers and providers engage in interactive dynamics: viewers benefit from increases in provider populations, while pr…
Learning from Streaming Data when Users Choose
Jinyan Su, Sarah Dean
In digital markets comprised of many competing services, each user chooses between multiple service providers according to their preferences, and the chosen service makes use of th…
Strategic Usage in a Multi-Learner Setting
Eliot Shekhtman, Sarah Dean
Real-world systems often involve some pool of users choosing between a set of services. With the increase in popularity of online learning algorithms, these services can now self-o…
Initializing Services in Interactive ML Systems for Diverse Users
Avinandan Bose, Mihaela Curmei, Daniel L. Jiang +4
This paper investigates ML systems serving a group of users, with multiple models/services, each aimed at specializing to a sub-group of users. We consider settings where upon depl…