Connor T. Jerzak

According to our database, Connor T. Jerzak authored at least 16 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

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

Samuel Grütter, Ethan Jerzak, Connor T. Jerzak

CoRR, April, 2026

Detecting and Mitigating Treatment Leakage in Text-Based Causal Inference: Distillation and Sensitivity Analysis.

Adel Daoud, Richard Johansson, Connor T. Jerzak

CoRR, January, 2026

FastRerandomize: Fast rerandomization using accelerated computing.

Rebecca Goldstein, Connor T. Jerzak, Aniket Kamat, Fucheng Warren Zhu

SoftwareX, 2026

Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis.

Markus B. Pettersson, Connor Thomas Jerzak, Adel Daoud

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

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

Satiyabooshan Murugaboopathy, Connor T. Jerzak, Adel Daoud

CoRR, August, 2025

Benchmarking Debiasing Methods for LLM-based Parameter Estimates.

Nicolas Audinet de Pieuchon, Adel Daoud, Connor Thomas Jerzak, Moa Johansson, Richard Johansson

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Optimizing Multi-Scale Representations to Detect Effect Heterogeneity Using Earth Observation and Computer Vision: Applications to Two Anti-Poverty RCTs.

Fucheng Warren Zhu, Connor Thomas Jerzak, Adel Daoud

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

2024

Encoding Multi-level Dynamics in Effect Heterogeneity Estimation.

Fucheng Warren Zhu, Connor T. Jerzak, Adel Daoud

CoRR, 2024

Planetary Causal Inference: Implications for the Geography of Poverty.

Kazuki Sakamoto, Connor T. Jerzak, Adel Daoud

CoRR, 2024

Can Large Language Models (or Humans) Distill Text?

Nicolas Audinet de Pieuchon, Adel Daoud, Connor Thomas Jerzak, Moa Johansson, Richard Johansson

CoRR, 2024

2023

CausalImages: An R Package for Causal Inference with Earth Observation, Bio-medical, and Social Science Images.

Connor T. Jerzak, Adel Daoud

CoRR, 2023

Linking Datasets on Organizations Using Half A Billion Open Collaborated Records.

Brian Libgober, Connor T. Jerzak

CoRR, 2023

Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities.

Connor T. Jerzak, Fredrik D. Johansson, Adel Daoud

CoRR, 2023

Image-based Treatment Effect Heterogeneity.

Connor Thomas Jerzak, Fredrik Daniel Johansson, Adel Daoud

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africa.

Connor T. Jerzak, Fredrik Johansson, Adel Daoud

CoRR, 2022

Conceptualizing Treatment Leakage in Text-based Causal Inference.

Adel Daoud, Connor T. Jerzak, Richard Johansson

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022