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

385 papers, page 2 of 8

51. ICML 2026Learning Treatment Allocations with Risk Control Under Partial Identifiability
52. ICML 2026Learning Treatment Representations for Downstream Instrumental Variable Regression
53. ICML 2026Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions
54. ICML 2026Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments
55. ICML 2026On the Effect of Misspecifying the Embedding Dimension in Low-rank Network Models
56. ICML 2026Rank-Learner: Orthogonal Ranking of Treatment Effects
57. ICML 2026Signal Strength Estimation in Logistic Regression Using Data Splitting
58. ICML 2026Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
59. ICML 2026Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings
60. ICML 2026Towards a Holistic Understanding of Selection Bias for Causal Effect Identification
61. ICML 2026Treatment Responder Classification with Abstention
62. ICML 2026Unveiling Prior-Data Fitted Networks on Causal Effect Estimation: Pre-Training or Fine-Tuning?
63. NeurIPS 2026Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring
64. NeurIPS 2026Automated Causal Effect Estimation through Self-Evolving AI
65. NeurIPS 2026Bayesian Causal Experimental Design for CATE Estimation under Noncompliance
66. NeurIPS 2026Bayesian Causal Stress Testing: Posterior Fragility of Treatment-Effect Conclusions
67. NeurIPS 2026Causal Effect Identification with a Single Agnostic Proxy
68. NeurIPS 2026Conditional Counterfactual Mean Embeddings: Doubly Robust Estimation and Learning Rates
69. NeurIPS 2026Conservative Continuous-Time Treatment Optimization
70. NeurIPS 2026Conservative neural posterior estimation via distributionally robust training
71. NeurIPS 2026CUVET: A Partitioning Approach for Continuous Treatment Assignment At Scale
72. NeurIPS 2026DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experiments
73. NeurIPS 2026Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
74. NeurIPS 2026Decision-Aware Proximal Bridge Learning for Optimal Treatment Selection
75. NeurIPS 2026Distribution-First Framework for Learning Risk-Sensitive Individualized Treatment Rules
76. NeurIPS 2026Distributional Estimation of 3D Object Orientation
77. NeurIPS 2026Dynamic Treatment on Networks
78. NeurIPS 2026Effect-Level Validation for Causal Discovery in Interactive Telemetry
79. NeurIPS 2026Explainability matters: The effect of liability rules on the healthcare sector
80. NeurIPS 2026Fair Division of Work in Collaborative Mean Estimation via Bargaining
81. NeurIPS 2026FMMI: Flow Matching Mutual Information Estimation
82. NeurIPS 2026Focusable Monocular Depth Estimation
83. NeurIPS 2026Free energy Estimation on Any State Space
84. NeurIPS 2026From Persistence to Survival: Hypothesis Testing, Effect Sizes and Vectorisation for Topological Features
85. NeurIPS 2026Global Importance Estimation for KV Cache Eviction
86. NeurIPS 2026Impossibility of Distribution-Free Predictive Inference for Individual Treatment Effects
87. NeurIPS 2026Inference and estimation with unidentifiable latent treatment effects
88. NeurIPS 2026Integrating digital twins with randomized experiments
89. NeurIPS 2026Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
90. NeurIPS 2026Learning Modular Addition with Auxiliary Modulus
91. NeurIPS 2026Metric Depth Estimation from Arbitrarily Degraded Low-Resolution Depth Prompts
92. NeurIPS 2026Mitigating Data Heterogeneity Effect in Client-Reshuffling-Based Federated Learning
93. NeurIPS 2026MSConsensus: A Hundred-Million-Scale, Batch-Effect–Suppressed Dataset and Benchmark for Proteomics Machine Learning
94. NeurIPS 2026Negation Neglect: When models fail to learn negations in training
95. NeurIPS 2026On the Effect of Token Correlations on Semantic Transfer in Transformers
96. NeurIPS 2026Phase Transitions in Heavy-Tailed Mean Estimation under $\ell_p$ Norms
97. NeurIPS 2026Provably Accurate Shapley Value Estimation in High Dimensions via Sparse Leverage Sampling
98. NeurIPS 2026Roll2Depth: Zero-Shot Metric Depth Estimation Exploiting Camera's Rolling Shutter Effect
99. NeurIPS 2026Settling Pure Differentially Private Covariance Estimation
100. NeurIPS 2026Spectral Estimation with Deformed Decompression

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.