Treatment Effect papers, 2023–2026

Key findings

• Treatment Effect went from 75 papers in 2023 to 106 in 2026, roughly 1.4x in three years.
• NeurIPS publishes the most Treatment Effect work: 131 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with General ML · unsupervised and semisupervised learning: papers tagged with both rose from 3 in 2023 to 10 in 2026.
• Among the 5 topics under Causal and Fairness, it ranks #2 by 2026 paper count; the fastest grower in the group, Causal Discovery, is up 2.4x versus 1.4x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring
• ICML 2026Causal Effect Identifiability in the Presence of Latent Confounders Without Auxiliary Variables
• ICLR 2026ActiveCQ: Active Estimation of Causal Quantities
• CVPR 2026Event Stream Filtering via Probability Flux Estimation
• NeurIPS 2025Born a Transformer -- Always a Transformer? On the Effect of Pretraining on Architectural Abilities
• ICML 2025A Meta-learner for Heterogeneous Effects in Difference-in-Differences
• ICLR 2025Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables
• CVPR 2025Any6D: Model-free 6D Pose Estimation of Novel Objects
• NeurIPS 2024Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
• ICML 2024A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
• ICLR 2024A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
• CVPR 2024LightOctree: Lightweight 3D Spatially-Coherent Indoor Lighting Estimation
• NeurIPS 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effect
• ICML 2023A Three-regime Model of Network Pruning
• ICLR 2023Causal Estimation for Text Data with (Apparent) Overlap Violations
• CVPR 2023HRDFuse: Monocular 360deg Depth Estimation by Collaboratively Learning Holistic-With-Regional Depth Distributions
• NeurIPS 2026Automated Causal Effect Estimation through Self-Evolving AI
• ICML 2026Causal-EPIG: Causally Aligned Active CATE Estimation
• ICLR 2026Foundation Models for Causal Inference via Prior-Data Fitted Networks
• CVPR 2026The Invisible Gorilla Effect in Out-of-distribution Detection

All Treatment Effect papers

21 papers, page 1 of 1

1. NeurIPS 2023A Cross-Moment Approach for Causal Effect Estimation
2. NeurIPS 2023Adversarial Counterfactual Environment Model Learning
3. NeurIPS 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effect
4. NeurIPS 2023Causal Effect Identification in Uncertain Causal Networks
5. NeurIPS 2023Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations
6. NeurIPS 2023Conformal Meta-learners for Predictive Inference of Individual Treatment Effects
7. NeurIPS 2023Data Pruning via Moving-one-Sample-out
8. NeurIPS 2023Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
9. NeurIPS 2023FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation
10. NeurIPS 2023Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation
11. NeurIPS 2023Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge
12. NeurIPS 2023Minimax-Optimal Location Estimation
13. NeurIPS 2023Multiply Robust Federated Estimation of Targeted Average Treatment Effects
14. NeurIPS 2023Non-stationary Experimental Design under Linear Trends
15. NeurIPS 2023On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis
16. NeurIPS 2023Optimal Transport for Treatment Effect Estimation
17. NeurIPS 2023Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making
18. NeurIPS 2023Optimal Treatment Regimes for Proximal Causal Learning
19. NeurIPS 2023RegBN: Batch Normalization of Multimodal Data with Regularization
20. NeurIPS 2023Sharp Bounds for Generalized Causal Sensitivity Analysis
21. NeurIPS 2023The Tunnel Effect: Building Data Representations in Deep Neural Networks

FAQ

How many Treatment Effect papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

385 in total: 75 in 2023, 106 in 2024, 98 in 2025, 106 in 2026.

How many Treatment Effect papers are at NeurIPS 2026?

NeurIPS 2026 has 44 Treatment Effect papers, versus 34 the year before.

How many Treatment Effect papers are at ICLR 2026?

ICLR 2026 has 18 Treatment Effect papers, versus 16 the year before.

How many Treatment Effect papers are at ICML 2026?

ICML 2026 has 27 Treatment Effect papers, versus 31 the year before.

How many Treatment Effect papers are at CVPR 2026?

CVPR 2026 has 17 Treatment Effect papers, versus 17 the year before.

Which conference publishes the most Treatment Effect papers?

NeurIPS, with 131 papers from 2023 to 2026.