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

283 papers, page 6 of 6

251. ICLR 2023How robust is unsupervised representation learning to distribution shift?
252. ICLR 2023How Sharpness-Aware Minimization Minimizes Sharpness?
253. ICLR 2023Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data
254. ICLR 2023Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
255. ICLR 2023Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization
256. ICLR 2023Is Forgetting Less a Good Inductive Bias for Forward Transfer?
257. ICLR 2023LAVA: Data Valuation without Pre-Specified Learning Algorithms
258. ICLR 2023Learning Language Representations with Logical Inductive Bias
259. ICLR 2023Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets
260. ICLR 2023Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent
261. ICLR 2023MEDFAIR: Benchmarking Fairness for Medical Imaging
262. ICLR 2023Mitigating Dataset Bias by Using Per-Sample Gradient
263. ICLR 2023Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability
264. ICLR 2023Sequential Gradient Coding For Straggler Mitigation
265. ICLR 2023TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations
266. ICLR 2023The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks
267. ICLR 2023The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks
268. ICLR 2023Tuning Frequency Bias in Neural Network Training with Nonuniform Data
269. ICML 2023FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction
270. ICML 2023Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
271. ICML 2023Improving Fair Training under Correlation Shifts
272. ICML 2023Men Also Do Laundry: Multi-Attribute Bias Amplification
273. ICML 2023Naive imputation implicitly regularizes high-dimensional linear models
274. ICML 2023Near-Optimal Quantum Coreset Construction Algorithms for Clustering
275. ICML 2023Statistical Indistinguishability of Learning Algorithms
276. ICML 2023Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias
277. NeurIPS 2023Fast Model DeBias with Machine Unlearning
278. NeurIPS 2023Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability
279. NeurIPS 2023Mitigating Source Bias for Fairer Weak Supervision
280. NeurIPS 2023Reproducibility Study of “Quantifying Societal Bias Amplification in Image Captioning”
281. NeurIPS 2023Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition
282. NeurIPS 2023Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples
283. NeurIPS 2023The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks

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.