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Remembering for the right reasons: Explanations reduce catastrophic forgetting

https://doi.org/10.1002/ail2.44
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/ail2.44openalex-snapshot
Remembering for the right reasons: Explanations reduce catastrophic forgetting
inferredcites →https://doi.org/10.1007/978-3-030-01258-8_15openalex-snapshot
End-to-End Incremental Learning
inferredcites →https://doi.org/10.1007/978-3-030-58621-8_23openalex-snapshot
Adversarial Continual Learning
inferredcites →https://doi.org/10.1007/978-3-319-10590-1_53openalex-snapshot
Visualizing and Understanding Convolutional Networks
inferredcites →https://doi.org/10.1007/978-3-319-46493-0_37openalex-snapshot
Learning Without Forgetting
inferredcites →https://doi.org/10.1007/s11263-017-1059-xopenalex-snapshot
Top-Down Neural Attention by Excitation Backprop
inferredcites →https://doi.org/10.1016/0921-8890(95)00004-yopenalex-snapshot
Lifelong robot learning
inferredcites →https://doi.org/10.1016/s0079-7421(08)60536-8openalex-snapshot
Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem
inferredcites →https://doi.org/10.1037/0033-295x.102.3.419openalex-snapshot
Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory.
inferredcites →https://doi.org/10.1073/pnas.1611835114openalex-snapshot
Overcoming catastrophic forgetting in neural networks
inferredcites →https://doi.org/10.1080/09540099550039318openalex-snapshot
Catastrophic Forgetting, Rehearsal and Pseudorehearsal
inferredcites →https://doi.org/10.1109/access.2019.2963055openalex-snapshot
Regional Multi-Scale Approach for Visually Pleasing Explanations of Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2016.319openalex-snapshot
Learning Deep Features for Discriminative Localization
inferredcites →https://doi.org/10.1109/cvpr.2017.587openalex-snapshot
iCaRL: Incremental Classifier and Representation Learning
inferredcites →https://doi.org/10.1109/cvpr.2018.00810openalex-snapshot
PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning
inferredcites →https://doi.org/10.1109/cvpr.2019.00046openalex-snapshot
Large Scale Incremental Learning
inferredcites →https://doi.org/10.1109/cvpr.2019.00528openalex-snapshot
Learning Without Memorizing
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01220openalex-snapshot
Few-Shot Class-Incremental Learning
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01360openalex-snapshot
iTAML: An Incremental Task-Agnostic Meta-learning Approach
inferredcites →https://doi.org/10.1109/iccv.2009.5459469openalex-snapshot
What is the best multi-stage architecture for object recognition?
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/iccv.2019.00268openalex-snapshot
Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded
inferredcites →https://doi.org/10.1109/icra.2019.8793982openalex-snapshot
Memory Efficient Experience Replay for Streaming Learning
inferredcites →https://doi.org/10.1109/wacv.2018.00097openalex-snapshot
Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks
inferredcites →https://doi.org/10.1145/2939672.2939778openalex-snapshot
"Why Should I Trust You?"
inferredcites →https://doi.org/10.24963/ijcai.2017/371openalex-snapshot
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations
inferredcites →https://doi.org/10.48550/arxiv.0912.1128openalex-snapshot
How to Explain Individual Classification Decisions
inferredcites →https://doi.org/10.48550/arxiv.1412.6806openalex-snapshot
Striving for Simplicity: The All Convolutional Net
inferredcites →https://doi.org/10.48550/arxiv.1412.6856openalex-snapshot
Object Detectors Emerge in Deep Scene CNNs
inferredcites →https://doi.org/10.48550/arxiv.1605.01713openalex-snapshot
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
inferredcites →https://doi.org/10.48550/arxiv.1611.07450openalex-snapshot
Grad-CAM: Why did you say that?
inferredcites →https://doi.org/10.48550/arxiv.1701.08734openalex-snapshot
PathNet: Evolution Channels Gradient Descent in Super Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1703.01365openalex-snapshot
Axiomatic Attribution for Deep Networks
inferredcites →https://doi.org/10.48550/arxiv.1703.04200openalex-snapshot
Continual Learning Through Synaptic Intelligence
inferredcites →https://doi.org/10.48550/arxiv.1704.02685openalex-snapshot
Learning Important Features Through Propagating Activation Differences
inferredcites →https://doi.org/10.48550/arxiv.1706.03825openalex-snapshot
SmoothGrad: removing noise by adding noise
inferredcites →https://doi.org/10.48550/arxiv.1710.10368openalex-snapshot
Deep Generative Dual Memory Network for Continual Learning
inferredcites →https://doi.org/10.48550/arxiv.1711.10563openalex-snapshot
FearNet: Brain-Inspired Model for Incremental Learning
inferredcites →https://doi.org/10.48550/arxiv.1806.07421openalex-snapshot
RISE: Randomized Input Sampling for Explanation of Black-box Models
inferredcites →https://doi.org/10.48550/arxiv.1810.03292openalex-snapshot
Sanity Checks for Saliency Maps
inferredcites →https://doi.org/10.48550/arxiv.1812.00420openalex-snapshot
Efficient Lifelong Learning with A-GEM
inferredcites →https://doi.org/10.48550/arxiv.1908.03265openalex-snapshot
On the Variance of the Adaptive Learning Rate and Beyond
inferredcites →https://doi.org/10.57702/i9oeewf6openalex-snapshot
Caltech-UCSD Birds-200-2011 Dataset
inferredcites →https://doi.org/10.57702/zp44cu3gopenalex-snapshot
Learning Multiple Layers of Features from Tiny Images

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/ail2.61openalex-snapshot
DARPA 's explainable AI ( XAI ) program: A retrospective
inferred← citeshttps://doi.org/10.1002/widm.70046openalex-snapshot
XAI ‐Guided Continual Learning: Rationale, Methods, and Future Directions
inferred← citeshttps://doi.org/10.1007/978-3-031-13324-4_46openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-20053-3_10openalex-snapshot
Anti-retroactive Interference for Lifelong Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-46314-3_13openalex-snapshot
Class Incremental Learning with Important and Diverse Memory
inferred← citeshttps://doi.org/10.1007/978-3-031-78189-6_11openalex-snapshot
ESL: Explain to Improve Streaming Learning for Transformers
inferred← citeshttps://doi.org/10.1007/978-3-031-94748-3_20openalex-snapshot
From Birth to Loss of Representations in Artificial Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-032-00986-9_29openalex-snapshot
Entropy-Guided Self-regulated Learning Without Forgetting for Distribution-Shift Continual Learning with Blurred Task Boundaries
inferred← citeshttps://doi.org/10.1007/s00138-023-01420-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10115-025-02589-xopenalex-snapshot
A comprehensive survey of stream reasoning and its integration with knowledge graphs
inferred← citeshttps://doi.org/10.1007/s13735-023-00279-4openalex-snapshot
Few-shot and meta-learning methods for image understanding: a survey
inferred← citeshttps://doi.org/10.1016/b978-0-443-36370-2.00016-5openalex-snapshot
Internet of medical things for accurate and sustainable medical decision making in heart disease management
inferred← citeshttps://doi.org/10.1016/j.neucom.2023.126579openalex-snapshot
Class Incremental Learning based on Identically Distributed Parallel One-Class Classifiers
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.127960openalex-snapshot
Drifting explanations in continual learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128217openalex-snapshot
Synergistic insights: Exploring continuous learning and explainable AI in handwritten digit recognition
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128923openalex-snapshot
Potential Knowledge Extraction Network for Class-Incremental Learning
inferred← citeshttps://doi.org/10.1049/cvi2.70013openalex-snapshot
Recent Advances of Continual Learning in Computer Vision: An Overview
inferred← citeshttps://doi.org/10.1109/access.2021.3140175openalex-snapshot
A Metaverse: Taxonomy, Components, Applications, and Open Challenges
inferred← citeshttps://doi.org/10.1109/access.2025.3555539openalex-snapshot
A Review of Short-Term, Long-Term, and Memory Consolidation Mechanisms in the Hippocampus and Cerebral Cortex
inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.01640openalex-snapshot
Continual Learning via Bit-Level Information Preserving
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On Guiding Visual Attention with Language Specification
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PIVOT: Prompting for Video Continual Learning
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D3Former: Debiased Dual Distilled Transformer for Incremental Learning
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Memory Population in Continual Learning via Outlier Elimination
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Adversarially Robust Continual Learning
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Continual Learning: A Review of Techniques, Challenges, and Future Directions
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CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning
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A Comprehensive Survey of Continual Learning: Theory, Method and Application
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Saliency Guided Experience Packing for Replay in Continual Learning
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Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
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A Protocol for Continual Explanation of SHAP
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Sparse Coding in a Dual Memory System for Lifelong Learning
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BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief
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Modern Continual Learning with Foundation Models, Evaluation Challenges, and Future Directions
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Continual Learning via Bit-Level Information Preserving
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Optimizing Reusable Knowledge for Continual Learning via Metalearning
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When Continual Learning Meets Robotic Grasp Detection: A Novel Benchmark on the Jacquard Dataset
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