PMF-CL derives Pareto-minimal-forgetting algorithms for linear/basis-function regression and quadratic-bounded losses like logistic regression, achieving static O(d²) memory for d-parameter models.
arXiv:2506.03320, https://arxiv.org/abs/2506
2 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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ANNEAL uses Failure-Driven Knowledge Acquisition to localize faults, generate constrained symbolic patches, and validate them before committing to a process knowledge graph, eliminating recurring failures where baselines do not.
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PMF-CL: Pareto-Minimal-Forgetting Continual Learner for Conflicting Tasks
PMF-CL derives Pareto-minimal-forgetting algorithms for linear/basis-function regression and quadratic-bounded losses like logistic regression, achieving static O(d²) memory for d-parameter models.
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ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning
ANNEAL uses Failure-Driven Knowledge Acquisition to localize faults, generate constrained symbolic patches, and validate them before committing to a process knowledge graph, eliminating recurring failures where baselines do not.