Operationalising the Right to be Forgotten in LLMs: A Lightweight Sequential Unlearning Framework for Privacy-Aligned Deployment in Politically Sensitive Environments explores A lightweight sequential unlearning framework for LLMs that enables privacy-aligned deployment by selectively suppressing sensitive data without compromising general language capabilities.. Commercial viability score: 7/10 in LLM Privacy.
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Canonical route: /paper/operationalising-the-right-to-be-forgotten-in-llms-a-lightweight-sequential-unlearning-framework-for-privacy-aligned-dep
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Agent Handoff
Canonical ID operationalising-the-right-to-be-forgotten-in-llms-a-lightweight-sequential-unlearning-framework-for-privacy-aligned-dep | Route /paper/operationalising-the-right-to-be-forgotten-in-llms-a-lightweight-sequential-unlearning-framework-for-privacy-aligned-dep
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/operationalising-the-right-to-be-forgotten-in-llms-a-lightweight-sequential-unlearning-framework-for-privacy-aligned-depMCP example
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}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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Dimensions overall score 7.0
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