Cover Image

Mitigating Spurious Background Bias in Multimedia Recognition with Disentangled Concept Bottlenecks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Gaoxiang, Lai, Songning, Yue, Yutao
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Guarding the Gate: ConceptGuard Battles Concept-Level Backdoors in Concept Bottleneck Models
by: Lai, Songning, et al.
Published: (2024)

Wolf2Pack: The AutoFusion Framework for Dynamic Parameter Fusion
by: Tian, Bowen, et al.
Published: (2024)

Learning New Concepts, Remembering the Old: Continual Learning for Multimodal Concept Bottleneck Models
by: Lai, Songning, et al.
Published: (2024)

Superclass-Guided Representation Disentanglement for Spurious Correlation Mitigation
by: Liu, Chenruo, et al.
Published: (2025)

Mitigating Bias in Concept Bottleneck Models for Fair and Interpretable Image Classification
by: Tong, Schrasing, et al.
Published: (2026)

Unsupervised Concept Discovery Mitigates Spurious Correlations
by: Arefin, Md Rifat, et al.
Published: (2024)

CAT: Concept-level backdoor ATtacks for Concept Bottleneck Models
by: Lai, Songning, et al.
Published: (2024)

Constructing Concept-based Models to Mitigate Spurious Correlations with Minimal Human Effort
by: Kim, Jeeyung, et al.
Published: (2024)

Stable Vision Concept Transformers for Medical Diagnosis
by: Hu, Lijie, et al.
Published: (2025)

SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
by: Wang, Wenjing, et al.
Published: (2026)

Benchmarking Spurious Bias in Few-Shot Image Classifiers
by: Zheng, Guangtao, et al.
Published: (2024)

Enabling Visual Recognition at Radio Frequency
by: Lai, Haowen, et al.
Published: (2024)

Concept Bottleneck Models Without Predefined Concepts
by: Schrodi, Simon, et al.
Published: (2024)

Flexible Concept Bottleneck Model
by: Du, Xingbo, et al.
Published: (2025)

Hyperbolic Concept Bottleneck Models
by: Uyterlinde, Daniel, et al.
Published: (2026)

Disentangled Representation Learning with Transmitted Information Bottleneck
by: Dang, Zhuohang, et al.
Published: (2023)

IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
by: Hu, Zhangyi, et al.
Published: (2025)

Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
by: Noohdani, Fahimeh Hosseini, et al.
Published: (2024)

Learning Robust Classifiers with Self-Guided Spurious Correlation Mitigation
by: Zheng, Guangtao, et al.
Published: (2024)

Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
by: Yang, Yu, et al.
Published: (2023)

The Instinctive Bias: Spurious Images lead to Illusion in MLLMs
by: Han, Tianyang, et al.
Published: (2024)

On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs
by: Schwalbe, Gesina, et al.
Published: (2025)

Interpretable and Steerable Concept Bottleneck Sparse Autoencoders
by: Kulkarni, Akshay, et al.
Published: (2025)

Towards Faithful Multimodal Concept Bottleneck Models
by: Moreau, Pierre, et al.
Published: (2026)

Debugging Concept Bottleneck Models through Removal and Retraining
by: Enouen, Eric, et al.
Published: (2025)

Semi-supervised Concept Bottleneck Models
by: Hu, Lijie, et al.
Published: (2024)

Interpretable Generative Models through Post-hoc Concept Bottlenecks
by: Kulkarni, Akshay, et al.
Published: (2025)

Editable Concept Bottleneck Models
by: Hu, Lijie, et al.
Published: (2024)

MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations
by: Jin, Qixuan, et al.
Published: (2024)

Faster ISNet for Background Bias Mitigation on Deep Neural Networks
by: Bassi, Pedro R. A. S., et al.
Published: (2024)

VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance
by: Srivastava, Divyansh, et al.
Published: (2024)

From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition
by: Qraitem, Maan, et al.
Published: (2023)

Disentangled Representation Learning via Modular Compositional Bias
by: Jung, Whie, et al.
Published: (2025)

Zero-shot Concept Bottleneck Models
by: Yamaguchi, Shin'ya, et al.
Published: (2025)

Process-Guided Concept Bottleneck Model
by: Asiyabi, Reza M., et al.
Published: (2026)

Concept Inconsistency in Dermoscopic Concept Bottleneck Models: A Rough-Set Analysis of the Derm7pt Dataset
by: Nápoles, Gonzalo, et al.
Published: (2026)

Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound
by: Bunnell, Arianna, et al.
Published: (2024)

CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning
by: Javadi, Amirhosein, et al.
Published: (2026)

Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs
by: Hasanebrahimi, Afsaneh, et al.
Published: (2026)

MM-SpuBench: Towards Better Understanding of Spurious Biases in Multimodal LLMs
by: Ye, Wenqian, et al.
Published: (2024)