In an exact-fit linear regime with i.i.d. tasks from distribution Π, forgetting obeys a recursive spectral operator whose asymptotic convergence rate is governed by geometric properties of Π.
https: //arxiv.org/abs/2004.07211
3 Pith papers cite this work. Polarity classification is still indexing.
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AIM applies modality-specific masks to balance stability and plasticity in asymmetric VLMs, achieving SOTA average performance and reduced forgetting on continual VQA v2 and GQA while preserving generalization to novel compositions.
BRAIN uses bias-mitigation continual learning with a new de-bias contrastive loss and angular forgetting mitigation to achieve SOTA performance on vision-brain understanding benchmarks despite brain signal inconsistencies across sessions.
citing papers explorer
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From Order to Distribution: A Spectral Characterization of Forgetting in Continual Learning
In an exact-fit linear regime with i.i.d. tasks from distribution Π, forgetting obeys a recursive spectral operator whose asymptotic convergence rate is governed by geometric properties of Π.
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AIM: Asymmetric Information Masking for Visual Question Answering Continual Learning
AIM applies modality-specific masks to balance stability and plasticity in asymmetric VLMs, achieving SOTA average performance and reduced forgetting on continual VQA v2 and GQA while preserving generalization to novel compositions.
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BRAIN: Bias-Mitigation Continual Learning Approach to Vision-Brain Understanding
BRAIN uses bias-mitigation continual learning with a new de-bias contrastive loss and angular forgetting mitigation to achieve SOTA performance on vision-brain understanding benchmarks despite brain signal inconsistencies across sessions.