Pre-trained models
PulseAugur coverage of Pre-trained models — every cluster mentioning Pre-trained models across labs, papers, and developer communities, ranked by signal.
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New research reframes continual learning beyond forgetting and plasticity · 5 sources tracked
Recent research explores new facets of continual learning, moving beyond traditional challenges like catastrophic forgetting and plasticity loss. One paper introduces "data co-observation" as a distinct factor, demonstr…
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New method tackles knowledge forgetting in incremental learning
Researchers have introduced a novel approach called Non-Forgetting Allocation with Bi-Level Competition (NoFA-BC) to enhance Class-Incremental Learning (CIL) with pre-trained models. This method addresses the issue of k…
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New SoTU method enhances continual learning by tuning sparse orthogonal parameters
Researchers have introduced SoTU, a novel method for continual learning that addresses catastrophic forgetting in pre-trained models. Unlike existing approaches that use additional adapters or prompts, SoTU focuses on m…