most citedMiniMax Learning of Interpretable Factored Stochastic Policies from Conjoint Data, with Uncertainty Quantification

1 citations · 1 across the 4 of their papers we have counts for

collaborators

15 papers

cs.AI2026

When Many Answers Are Valid, Voting Fails: Symbolic Verification for Best-of-K Causal Reasoning in LLMs

Omatharv Bharat Vaidya, Connor Thomas Jerzak, Zayne Rea Sprague +2

Self-consistency assumes the most frequent answer among sampled reasoning traces is the most reliable, but this can fail in causal reasoning: samples often repeat the same confound…

cs.AI2026

Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty?

Satiyabooshan Murugaboopathy, Connor T. Jerzak, Adel Daoud

We investigate whether socioeconomic indicators, like household wealth, leave recoverable informational imprints in both satellite imagery (capturing features like buildings and ro…

econ.GN2026

Temporal Dynamics of Development Aid in Africa: Evidence from a Staggered Difference-in-Differences Study of China and World Bank Projects

Mattias Antar, Adel Daoud, Connor T. Jerzak

Subnational studies of aid effectiveness often rely on repeated cross-sections or nighttime lights, making it difficult to separate local treatment effects from baseline difference…

stat.ME20261 cited

MiniMax Learning of Interpretable Factored Stochastic Policies from Conjoint Data, with Uncertainty Quantification

Connor T. Jerzak, Priyanshi Chandra, Rishi Hazra

We study offline policy optimization over exponentially large factorial action spaces from randomized preference data, showing how conjoint experiments can estimate interpretable s…

cs.LG2026

Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms

Omatharv Bharat Vaidya, Connor T. Jerzak, Nhat Ho +1

We present a data-adaptive method for parameter-efficient fine-tuning of large neural networks. Standard low-rank adaptation methods improve efficiency by restricting each layer up…

cs.CL2026

Multiplication in Multimodal LLMs: Computation with Text, Image, and Audio Inputs

Samuel G. Balter, Ethan Jerzak, Connor T. Jerzak

Multimodal LLMs can accurately perceive numerical content across modalities yet fail to perform exact multi-digit multiplication when the identical underlying arithmetic problem is…