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 4 of 6

151. NeurIPS 2025Robust Graph Condensation via Classification Complexity Mitigation
152. NeurIPS 2025Silencer: From Discovery to Mitigation of Self-Bias in LLM-as-Benchmark-Generator
153. NeurIPS 2025Tackling Biased Evaluators in Dueling Bandits
154. NeurIPS 2025The Implicit Bias of Structured State Space Models Can Be Poisoned With Clean Labels
155. NeurIPS 2025The Persistence of Neural Collapse Despite Low-Rank Bias
156. NeurIPS 2025Training the Untrainable: Introducing Inductive Bias via Representational Alignment
157. NeurIPS 2025TranSUN: A Preemptive Paradigm to Eradicate Retransformation Bias Intrinsically from Regression Models in Recommender Systems
158. NeurIPS 2025Uncovering the Spectral Bias in Diagonal State Space Models
159. NeurIPS 2025Unveiling Extraneous Sampling Bias with Data Missing-Not-At-Random
160. NeurIPS 2025When majority rules, minority loses: bias amplification of gradient descent
161. CVPR 2024BA-SAM: Scalable Bias-Mode Attention Mask for Segment Anything Model
162. CVPR 2024Balancing Act: Distribution-Guided Debiasing in Diffusion Models
163. CVPR 2024Batch Normalization Alleviates the Spectral Bias in Coordinate Networks
164. CVPR 2024Diffeomorphic Template Registration for Atmospheric Turbulence Mitigation
165. CVPR 2024Enhancing Intrinsic Features for Debiasing via Investigating Class-Discerning Common Attributes in Bias-Contrastive Pair
166. CVPR 2024Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain
167. CVPR 2024FINER: Flexible Spectral-bias Tuning in Implicit NEural Representation by Variable-periodic Activation Functions
168. CVPR 2024Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincare Ball
169. CVPR 2024Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation
170. CVPR 2024On the Content Bias in Frechet Video Distance
171. CVPR 2024Robust Emotion Recognition in Context Debiasing
172. CVPR 2024Spatio-Temporal Turbulence Mitigation: A Translational Perspective
173. CVPR 2024Would Deep Generative Models Amplify Bias in Future Models?
174. ICLR 2024A 2-Dimensional State Space Layer for Spatial Inductive Bias
175. ICLR 2024Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
176. ICLR 2024Debiasing Algorithm through Model Adaptation
177. ICLR 2024Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach
178. ICLR 2024Elucidating the Exposure Bias in Diffusion Models
179. ICLR 2024FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
180. ICLR 2024Implicit bias of SGD in $L_2$-regularized linear DNNs: One-way jumps from high to low rank
181. ICLR 2024Leveraging Uncertainty Estimates To Improve Classifier Performance
182. ICLR 2024On Bias-Variance Alignment in Deep Models
183. ICLR 2024On the Foundations of Shortcut Learning
184. ICLR 2024Post-hoc bias scoring is optimal for fair classification
185. ICLR 2024Procedural Fairness Through Decoupling Objectionable Data Generating Components
186. ICML 2024A Universal Class of Sharpness-Aware Minimization Algorithms
187. ICML 2024Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
188. ICML 2024Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
189. ICML 2024Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
190. ICML 2024Can Implicit Bias Imply Adversarial Robustness?
191. ICML 2024Convergence of Some Convex Message Passing Algorithms to a Fixed Point
192. ICML 2024Differentially Private Bias-Term Fine-tuning of Foundation Models
193. ICML 2024Discovering Bias in Latent Space: An Unsupervised Debiasing Approach
194. ICML 2024Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
195. ICML 2024Evaluating Model Bias Requires Characterizing its Mistakes
196. ICML 2024Feature Importance Disparities for Data Bias Investigations
197. ICML 2024How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
198. ICML 2024In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
199. ICML 2024Initial Guessing Bias: How Untrained Networks Favor Some Classes
200. ICML 2024Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters

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.