collaborators

5 papers

math.ST2026

The Statistical Cost of Adaptation in Multi-Source Transfer Learning

Abhinav Chakraborty, Subha Maity

Multi-source transfer learning can improve target-domain estimation by leveraging related source data, but its benefits depend on unknown source-to-target biases. This raises a fun…

stat.ML2025

Limitations of refinement methods for weak to strong generalization

Seamus Somerstep, Ya'acov Ritov, Mikhail Yurochkin +2

Standard techniques for aligning large language models (LLMs) utilize human-produced data, which could limit the capability of any aligned LLM to human level. Label refinement and…

stat.ML2025

CARROT: A Cost Aware Rate Optimal Router

Seamus Somerstep, Felipe Maia Polo, Allysson Flavio Melo de Oliveira +5

With the rapid growth in the number of Large Language Models (LLMs), there has been a recent interest in LLM routing, or directing queries to the cheapest LLM that can deliver a su…

stat.ML2025

Microfoundation Inference for Strategic Prediction

Daniele Bracale, Subha Maity, Felipe Maia Polo +3

Often in prediction tasks, the predictive model itself can influence the distribution of the target variable, a phenomenon termed performative prediction. Generally, this influence…

stat.ML2025

Learning the Distribution Map in Reverse Causal Performative Prediction

Daniele Bracale, Subha Maity, Moulinath Banerjee +1

In numerous predictive scenarios, the predictive model affects the sampling distribution; for example, job applicants often meticulously craft their resumes to navigate through a s…