偏见缓解论文趋势 2023–2026

主要结论

• 偏见缓解论文从 2023 年的 50 篇增长到 2026 年的 76 篇，三年间扩大到约 1.5 倍。
• ICLR 是发偏见缓解论文最多的会议，2023–2026 年共 85 篇，占四个会议总量的 30%。
• 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 15 篇。
• 在「因果与公平」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的因果发现是 2.4 倍，偏见缓解是 1.5 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部偏见缓解论文

共 85 篇，第 1 / 2 页

1. CVPR 2025ClearSight: Visual Signal Enhancement for Object Hallucination Mitigation in Multimodal Large Language Models
2. CVPR 2025D2SP: Dynamic Dual-Stage Purification Framework for Dual Noise Mitigation in Vision-based Affective Recognition.
3. CVPR 2025Data Distributional Properties As Inductive Bias for Systematic Generalization
4. CVPR 2025Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
5. CVPR 2025FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing
6. CVPR 2025Joint Vision-Language Social Bias Removal for CLIP
7. CVPR 2025Perceptual Inductive Bias Is What You Need Before Contrastive Learning
8. ICLR 2025A Decade's Battle on Dataset Bias: Are We There Yet?
9. ICLR 2025ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition
10. ICLR 2025Anti-Exposure Bias in Diffusion Models
11. ICLR 2025Balancing Bias in Two-sided Markets for Fair Stable Matchings
12. ICLR 2025Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation
13. ICLR 2025Bias Mitigation in Graph Diffusion Models
14. ICLR 2025Causally Motivated Sycophancy Mitigation for Large Language Models
15. ICLR 2025Efficient stagewise pretraining via progressive subnetworks
16. ICLR 2025Eliminating Position Bias of Language Models: A Mechanistic Approach
17. ICLR 2025Exploring the Camera Bias of Person Re-identification
18. ICLR 2025Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
19. ICLR 2025Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression
20. ICLR 2025Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
21. ICLR 2025Language Models Need Inductive Biases to Count Inductively
22. ICLR 2025Manifold Constraint Reduces Exposure Bias in Accelerated Diffusion Sampling
23. ICLR 2025MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation
24. ICLR 2025NoVo: Norm Voting off Hallucinations with Attention Heads in Large Language Models
25. ICLR 2025Post-hoc Reward Calibration: A Case Study on Length Bias
26. ICLR 2025SANER: Annotation-free Societal Attribute Neutralizer for Debiasing CLIP
27. ICLR 2025SEBRA : Debiasing through Self-Guided Bias Ranking
28. ICLR 2025Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late In Training
29. ICLR 2025Tuning Frequency Bias of State Space Models
30. ICLR 2025Unlearning-based Neural Interpretations
31. ICML 2025ADDQ: Adaptive distributional double Q-learning
32. ICML 2025Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning
33. ICML 2025Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and Remedies
34. ICML 2025Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
35. ICML 2025Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
36. ICML 2025Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks
37. ICML 2025Inductive Gradient Adjustment for Spectral Bias in Implicit Neural Representations
38. ICML 2025Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?
39. ICML 2025NeuronTune: Towards Self-Guided Spurious Bias Mitigation
40. ICML 2025On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback
41. ICML 2025On the Emergence of Position Bias in Transformers
42. ICML 2025Parametric Scaling Law of Tuning Bias in Conformal Prediction
43. ICML 2025Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It
44. ICML 2025Resolving Lexical Bias in Model Editing
45. ICML 2025Rethinking the Bias of Foundation Model under Long-tailed Distribution
46. ICML 2025SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification
47. ICML 2025Subgroups Matter for Robust Bias Mitigation
48. NeurIPS 2025A Black-Box Debiasing Framework for Conditional Sampling
49. NeurIPS 2025Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
50. NeurIPS 2025Approximate Gradient Coding for Distributed Learning with Heterogeneous Stragglers

常见问题

2023–2026 年四大会议一共有多少篇偏见缓解论文？

共 284 篇，按年份分别是 2023 年 50 篇、2024 年 73 篇、2025 年 85 篇、2026 年 76 篇。

NeurIPS 2026 有多少篇偏见缓解论文？

NeurIPS 2026 有 14 篇偏见缓解论文，上一届是 38 篇。

ICLR 2026 有多少篇偏见缓解论文？

ICLR 2026 有 24 篇偏见缓解论文，上一届是 23 篇。

ICML 2026 有多少篇偏见缓解论文？

ICML 2026 有 24 篇偏见缓解论文，上一届是 17 篇。

CVPR 2026 有多少篇偏见缓解论文？

CVPR 2026 有 14 篇偏见缓解论文，上一届是 7 篇。

哪个会议的偏见缓解论文最多？

ICLR，2023–2026 年共 85 篇。