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 5 of 6

201. ICML 2024Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
202. ICML 2024On the Implicit Bias of Adam
203. ICML 2024On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
204. ICML 2024Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
205. ICML 2024Simplicity Bias via Global Convergence of Sharpness Minimization
206. ICML 2024Statistical Inference Under Constrained Selection Bias
207. ICML 2024The Role of Learning Algorithms in Collective Action
208. ICML 2024Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
209. NeurIPS 2024A distributional simplicity bias in the learning dynamics of transformers
210. NeurIPS 2024Addressing Bias in Online Selection with Limited Budget of Comparisons
211. NeurIPS 2024Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families
212. NeurIPS 2024Bayesian Identification of the Hamiltonian Inductive Bias in Dynamical Systems
213. NeurIPS 2024Bias Detection via Signaling
214. NeurIPS 2024Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training
215. NeurIPS 2024Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
216. NeurIPS 2024Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise
217. NeurIPS 2024Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
218. NeurIPS 2024CultureLLM: Incorporating Cultural Differences into Large Language Models
219. NeurIPS 2024DeNetDM: Debiasing by Network Depth Modulation
220. NeurIPS 2024Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement
221. NeurIPS 2024FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation
222. NeurIPS 2024How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks
223. NeurIPS 2024Implicit Bias of Mirror Flow on Separable Data
224. NeurIPS 2024Improved Algorithms for Contextual Dynamic Pricing
225. NeurIPS 2024IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing
226. NeurIPS 2024Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?
227. NeurIPS 2024Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints
228. NeurIPS 2024Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz
229. NeurIPS 2024Temporally Consistent Atmospheric Turbulence Mitigation with Neural Representations
230. NeurIPS 2024The Implicit Bias of Adam on Separable Data
231. NeurIPS 2024The Implicit Bias of Gradient Descent on Separable Multiclass Data
232. NeurIPS 2024Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis
233. NeurIPS 2024Unveiling the Bias Impact on Symmetric Moral Consistency of Large Language Models
234. CVPR 2023Bias Mimicking: A Simple Sampling Approach for Bias Mitigation
235. CVPR 2023Bias-Eliminating Augmentation Learning for Debiased Federated Learning
236. CVPR 2023BiasAdv: Bias-Adversarial Augmentation for Model Debiasing
237. CVPR 2023BiasBed - Rigorous Texture Bias Evaluation
238. CVPR 2023Generative Bias for Robust Visual Question Answering
239. CVPR 2023Good Is Bad: Causality Inspired Cloth-Debiasing for Cloth-Changing Person Re-Identification
240. CVPR 2023Probabilistic Debiasing of Scene Graphs
241. CVPR 2023Reducing the Label Bias for Timestamp Supervised Temporal Action Segmentation
242. CVPR 2023Training Debiased Subnetworks With Contrastive Weight Pruning
243. ICLR 2023Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models
244. ICLR 2023Bias Propagation in Federated Learning
245. ICLR 2023Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems
246. ICLR 2023Delving into Semantic Scale Imbalance
247. ICLR 2023Everybody Needs Good Neighbours: An Unsupervised Locality-based Method for Bias Mitigation
248. ICLR 2023Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks
249. ICLR 2023FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
250. ICLR 2023How gradient estimator variance and bias impact learning in neural 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.