Conceptualizing Treatment Leakage in Text-based Causal Inference. - Adel Daoud; Connor T. Jerzak; Richard Johansson (NAACL-HLT, 2022)

Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africa. - Connor T. Jerzak; Fredrik Johansson 002; Adel Daoud (CoRR, 2022)

Image-based Treatment Effect Heterogeneity. - Connor Thomas Jerzak; Fredrik Daniel Johansson; Adel Daoud (CLeaR, 2023)

Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities. - Connor T. Jerzak; Fredrik D. Johansson; Adel Daoud (CoRR, 2023)

Linking Datasets on Organizations Using Half A Billion Open Collaborated Records. - Brian Libgober; Connor T. Jerzak (CoRR, 2023)

CausalImages: An R Package for Causal Inference with Earth Observation, Bio-medical, and Social Science Images. - Connor T. Jerzak; Adel Daoud (CoRR, 2023)

Can Large Language Models (or Humans) Distill Text? - Nicolas Audinet de Pieuchon; Adel Daoud; Connor Thomas Jerzak; Moa Johansson; Richard Johansson (CoRR, 2024)

Planetary Causal Inference: Implications for the Geography of Poverty. - Kazuki Sakamoto; Connor T. Jerzak; Adel Daoud (CoRR, 2024)

Encoding Multi-level Dynamics in Effect Heterogeneity Estimation. - Fucheng Warren Zhu; Connor T. Jerzak; Adel Daoud (CoRR, 2024)

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 (CLeaR, 2025)

Benchmarking Debiasing Methods for LLM-based Parameter Estimates. - Nicolas Audinet de Pieuchon; Adel Daoud; Connor T. Jerzak; Moa Johansson; Richard Johansson (CoRR, 2025)