:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Xinyu, Zhang, Xu, Chen, Can, Wang, Ren
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2511.21923
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
by: Cheng, Zelei, et al.
Published: (2024)

Dynamic Graph Information Bottleneck
by: Yuan, Haonan, et al.
Published: (2024)

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
by: Ren, Zhiyao, et al.
Published: (2025)

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics
by: Downer, Jane, et al.
Published: (2024)

Invisible Backdoor Attack Through Singular Value Decomposition
by: Chen, Wenmin, et al.
Published: (2024)

TimeX++: Learning Time-Series Explanations with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024)

Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck
by: Yang, Hao, et al.
Published: (2024)

TimeSieve: Extracting Temporal Dynamics through Information Bottlenecks
by: Feng, Ninghui, et al.
Published: (2024)

Bottleneck Tokens for Unified Multimodal Retrieval
by: Sun, Siyu, et al.
Published: (2026)

Learning Fair Graph Representations with Multi-view Information Bottleneck
by: Liu, Chuxun, et al.
Published: (2025)

Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency
by: Pal, Soumyadeep, et al.
Published: (2024)

PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection
by: Li, Wei, et al.
Published: (2024)

Glocal Information Bottleneck for Time Series Imputation
by: Yang, Jie, et al.
Published: (2025)

Emergent Low-Rank Training Dynamics in MLPs with Smooth Activations
by: Xu, Alec S., et al.
Published: (2026)

Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
by: Penaloza, Emiliano, et al.
Published: (2025)

The Interaction Bottleneck of Deep Neural Networks: Discovery, Proof, and Modulation
by: Deng, Huiqi, et al.
Published: (2025)

GlassMol: Interpretable Molecular Property Prediction with Concept Bottleneck Models
by: Rivera, Oscar, et al.
Published: (2026)

Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024)

IIB-LPO: Latent Policy Optimization via Iterative Information Bottleneck
by: Deng, Huilin, et al.
Published: (2026)

Enhancing Adversarial Transferability via Information Bottleneck Constraints
by: Qi, Biqing, et al.
Published: (2024)

DDTime: Dataset Distillation with Spectral Alignment and Information Bottleneck for Time-Series Forecasting
by: Li, Yuqi, et al.
Published: (2025)

Behavior Backdoor for Deep Learning Models
by: Wang, Jiakai, et al.
Published: (2024)

Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training
by: Kudo, Sota, et al.
Published: (2024)

Improving ARDS Diagnosis Through Context-Aware Concept Bottleneck Models
by: Narain, Anish, et al.
Published: (2025)

Causally-Aware Information Bottleneck for Domain Adaptation
by: Javidian, Mohammad Ali
Published: (2026)

Interpretable Prototype-based Graph Information Bottleneck
by: Seo, Sangwoo, et al.
Published: (2023)

Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking
by: Kong, Cong, et al.
Published: (2024)

Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models
by: Xiao, He, et al.
Published: (2025)

MemFly: On-the-Fly Memory Optimization via Information Bottleneck
by: Zhang, Zhenyuan, et al.
Published: (2026)

Learning from Complexity: Exploring Dynamic Sample Pruning of Spatio-Temporal Training
by: Chen, Wei, et al.
Published: (2026)

GaGSL: Global-augmented Graph Structure Learning via Graph Information Bottleneck
by: Li, Shuangjie, et al.
Published: (2024)

Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks
by: Zhao, Zhe, et al.
Published: (2024)

Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Models
by: Wu, Yudi, et al.
Published: (2025)

vTune: Verifiable Fine-Tuning for LLMs Through Backdooring
by: Zhang, Eva, et al.
Published: (2024)

Incremental Residual Concept Bottleneck Models
by: Shang, Chenming, et al.
Published: (2024)

Theoretical Modeling of Large Language Model Self-Improvement Training Dynamics Through Solver-Verifier Gap
by: Sun, Yifan, et al.
Published: (2025)

IBNorm: Information-Bottleneck Inspired Normalization for Representation Learning
by: Zou, Xiandong, et al.
Published: (2025)

XFACTORS: Disentangled Information Bottleneck via Contrastive Supervision
by: Myara, Alexandre, et al.
Published: (2026)

Beyond the False Trade-off: Adaptive EWC for Stealthy and Generalizable T2I Backdoors
by: Bowen, Lu, et al.
Published: (2026)

Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training
by: Zhao, Mengnan, et al.
Published: (2026)