arXiv (OAI Expanded)
open access
MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks
Graph data across diverse domains can expose valuable relational information to unauthorized representation learning, creating a pressing need for protection against such misuse. Unlearnable examples offer a data-level defense by perturbing a training release so that models trained on it fail to gen
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks#925258
- Beyond Outcomes: Dual-View Relational Learning for Efficient Agent Benchmarking#1013066
- Beyond Outcomes: Dual-View Relational Learning for Efficient Agent Benchmarking#965454
- Collective Counterfactual Planning: Coordination, Consent, and Verification under Representational Constraints#723343
- Connecting the Dots in Agentic AI Security: A Cross-Dimensional Threat Taxonomy, Evaluation Maturity, and Open Challenges#1050085
Record · ID 921022
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive