Bias Mitigation papers, 2023–2026

Key findings

• Bias Mitigation went from 50 papers in 2023 to 76 in 2026, roughly 1.5x in three years.
• ICLR publishes the most Bias Mitigation work: 85 papers from 2023 to 2026, 30% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 0 in 2023 to 15 in 2026.
• Among the 5 topics under Causal and Fairness, it ranks #4 by 2026 paper count; the fastest grower in the group, Causal Discovery, is up 2.4x versus 1.5x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Controlling for Omitted Variable Bias in Deep Neural Networks
• ICML 2026BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation
• ICLR 2026Bi-directional Bias Attribution: Debiasing Large Language Models without Modifying Prompts
• CVPR 2026BAMI Training-Free Bias Mitigation in GUI Grounding
• NeurIPS 2025Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
• ICML 2025Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and Remedies
• ICLR 2025ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition
• CVPR 2025Data Distributional Properties As Inductive Bias for Systematic Generalization
• NeurIPS 2024Bayesian Identification of the Hamiltonian Inductive Bias in Dynamical Systems
• ICML 2024Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
• ICLR 2024A 2-Dimensional State Space Layer for Spatial Inductive Bias
• CVPR 2024Diffeomorphic Template Registration for Atmospheric Turbulence Mitigation
• NeurIPS 2023Fast Model DeBias with Machine Unlearning
• ICML 2023FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction
• ICLR 2023Bias Propagation in Federated Learning
• CVPR 2023Bias Mimicking: A Simple Sampling Approach for Bias Mitigation
• NeurIPS 2026Empirical Bayes Rebiasing
• ICML 2026DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
• ICLR 2026BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses
• CVPR 2026Bias at the End of the Score

All Bias Mitigation papers

72 papers, page 2 of 2

51. ICML 2024Evaluating Model Bias Requires Characterizing its Mistakes
52. ICML 2024Feature Importance Disparities for Data Bias Investigations
53. ICML 2024How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
54. ICML 2024In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
55. ICML 2024Initial Guessing Bias: How Untrained Networks Favor Some Classes
56. ICML 2024Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters
57. ICML 2024Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
58. ICML 2024On the Implicit Bias of Adam
59. ICML 2024On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
60. ICML 2024Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
61. ICML 2024Simplicity Bias via Global Convergence of Sharpness Minimization
62. ICML 2024Statistical Inference Under Constrained Selection Bias
63. ICML 2024The Role of Learning Algorithms in Collective Action
64. ICML 2024Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
65. ICML 2023FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction
66. ICML 2023Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
67. ICML 2023Improving Fair Training under Correlation Shifts
68. ICML 2023Men Also Do Laundry: Multi-Attribute Bias Amplification
69. ICML 2023Naive imputation implicitly regularizes high-dimensional linear models
70. ICML 2023Near-Optimal Quantum Coreset Construction Algorithms for Clustering
71. ICML 2023Statistical Indistinguishability of Learning Algorithms
72. ICML 2023Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias

FAQ

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

284 in total: 50 in 2023, 73 in 2024, 85 in 2025, 76 in 2026.

How many Bias Mitigation papers are at NeurIPS 2026?

NeurIPS 2026 has 14 Bias Mitigation papers, versus 38 the year before.

How many Bias Mitigation papers are at ICLR 2026?

ICLR 2026 has 24 Bias Mitigation papers, versus 23 the year before.

How many Bias Mitigation papers are at ICML 2026?

ICML 2026 has 24 Bias Mitigation papers, versus 17 the year before.

How many Bias Mitigation papers are at CVPR 2026?

CVPR 2026 has 14 Bias Mitigation papers, versus 7 the year before.

Which conference publishes the most Bias Mitigation papers?

ICLR, with 85 papers from 2023 to 2026.