mlsanityData to 14 Oct 2026

Positive-incentive Noise

arXiv 2212.09541 ↗First posted 19 Dec 2022cs.LGcited by 39

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Abstract (arXiv)

Noise is conventionally viewed as a severe problem in diverse fields, e.g., engineering, learning systems. However, this paper aims to investigate whether the conventional proposition always holds. It begins with the definition of task entropy, which extends from the information entropy and measures the complexity of the task. After introducing the task entropy, the noise can be classified into two kinds, Positive-incentive noise (Pi-noise or π-noise) and pure noise, according to whether the noise can reduce the complexity of the task. Interestingly, as shown theoretically and empirically, even the simple random noise can be the π-noise that simplifies the task. π-noise offers new explanations for some models and provides a new principle for some fields, such as multi-task learning, adversarial training, etc. Moreover, it reminds us to rethink the investigation of noises.

Key facts. Cited by 39 papers in the map (data through 14 Oct 2026). Builds on 3 of its 25 references that are in the map. First posted on arXiv 19 Dec 2022.

Builds on

3 of 25 references.

References · 3

  1. 2014Explaining and Harnessing Adversarial Examplescited by 7,364
  2. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,475
  3. 2022Matrix Completion via Non-Convex Relaxation and Adaptive Correlation Learningcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 5; 2024: 3; 2025: 19; 2026: 12.

39 papers.

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  1. 2023On the Design Fundamentals of Diffusion Models: A Surveycited by 60
  2. 2025AI Flow: Perspectives, Scenarios, and Approachescited by 44
  3. 2023Variational Positive-incentive Noise: How Noise Benefits Modelscited by 38
  4. 2024Multi-granularity Correspondence Learning from Long-term Noisy Videoscited by 34
  5. 2024Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noisecited by 25
  6. 2025Learn Beneficial Noise as Graph Augmentationcited by 15
  7. 2025NFIG: Multi-Scale Autoregressive Image Generation via Frequency Orderingcited by 14
  8. 2025Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learningcited by 14
  9. 2025Object-AVEdit: An Object-level Audio-Visual Editing Modelcited by 14
  10. 2025Integrating Reinforcement Learning with Visual Generative Models: Foundations and Advancescited by 12
  11. 2023Complex Mixer for MedMNIST Classification Decathloncited by 6
  12. 2026Unison: Harmonizing Motion, Speech, and Sound for Human-Centric Audio-Video Generationcited by 6
27 more
  1. 2023NoisyNN: Exploring the Impact of Information Entropy Change in Learning Systemscited by 5
  2. 2026InteractiveAvatar: Real-Time Streaming Video Generation for Consistent and Intent-Aware Avatarscited by 5
  3. 2025AnchorFormer: Differentiable Anchor Attention for Efficient Vision Transformercited by 3
  4. 2025TableZoomer: A Collaborative Agent Framework for Large-scale Table Question Answeringcited by 3
  5. 2026Enhancing Neural Video Compression of Static Scenes with Positive-Incentive Noisecited by 3
  6. 2026Adaptive Layerwise Perturbation: Unifying Off-Policy Corrections for LLM RLcited by 3
  7. 2025Class-Aware Prototype Learning with Negative Contrast for Test-Time Adaptation of Vision-Language Modelscited by 2
  8. 2025GRPO-RM: Fine-Tuning Representation Models via GRPO-Driven Reinforcement Learningcited by 2
  9. 2026Generative Transmission: Rethinking Computation, Bandwidth, and Memory in Communicationcited by 2
  10. 2023Data-Centric Long-Tailed Image Recognitioncited by 1
  11. 2024Structuring the Processing Frameworks for Data Stream Evaluation and Applicationcited by 1
  12. 2025Unveiling Hidden Vulnerabilities in Digital Human Generation via Adversarial Attackscited by 1
  13. 2025Representation Discrepancy Bridging Method for Remote Sensing Image-Text Retrievalcited by 1
  14. 2025ERF-BA-TFD+: A Multimodal Model for Audio-Visual Deepfake Detectioncited by 1
  15. 2025ViewMask-1-to-3: Multi-View Consistent Image Generation via Multimodal Discrete Diffusion Modelscited by 1
  16. 2026Semantic-Aware Temporal Adaptation for UAV Anti-UAV Trackingcited by 1
  17. 2025Leveraging Noisy Manual Labels as Useful Information: An Information Fusion Approach for Enhanced Variable Selection in Penalized Logistic Regressioncited by 0
  18. 2025Real-Time Crowd Counting for Embedded Systems with Lightweight Architecturecited by 0
  19. 2025How Noise Benefits AI-generated Image Detectioncited by 0
  20. 2025Structure-Aware Prototype Guided Trusted Multi-View Classificationcited by 0
  21. 2025Multi-Intent Spoken Language Understanding: Methods, Trends, and Challengescited by 0
  22. 2026Noise-Robust Tiny Object Localization with Flowscited by 0
  23. 2026CSGaussian: Progressive Rate-Distortion Compression and Segmentation for 3D Gaussian Splattingcited by 0
  24. 2026Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domaincited by 0
  25. 2026Learning Graphs through Continuous Information Entropy Fieldscited by 0
  26. 2026Representation Learning in Diffusion and Flow-based Model: An Application Aspectcited by 0
  27. 2026Incentive Noise and Structural Prior Infusion for Multi-modal Object Re-Identificationcited by 0