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  3. KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Au
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KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation

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Viability
0.0/10

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Evidence fresh

Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: unverified

Freshness: fresh

Source paper: KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation

PDF: https://arxiv.org/pdf/2603.11501v1

Source count: 0

Coverage: 17%

Last proof check: 2026-04-02T02:30:40.136Z

Paper Conversation

Citation-first answers with explicit evidence receipts, disagreement handling, commercialization framing, and next actions.

Paper Mode

KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation

Overall score: 4/10
Lineage: ec6ac60bc371…
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Canonical Paper Receipt

Last verification: 2026-04-02T02:30:40.136Z

Freshness: fresh

Proof: unverified

Repo: missing

References: 0

Sources: 0

Coverage: 17%

Missingness
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Dimensions overall score 4.0

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Prior Work
PIDP-Attack: Combining Prompt Injection with Database Poisoning Attacks on Retrieval-Augmented Generation Systems
Score 4.0stable
Prior Work
Towards Secure Retrieval-Augmented Generation: A Comprehensive Review of Threats, Defenses and Benchmarks
Score 4.0stable
Higher Viability
RAGShield: Provenance-Verified Defense-in-Depth Against Knowledge Base Poisoning in Government Retrieval-Augmented Generation Systems
Score 7.0up
Higher Viability
Connect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation Systems
Score 5.0up
Higher Viability
Towards Robust Retrieval-Augmented Generation Based on Knowledge Graph: A Comparative Analysis
Score 7.0up
Higher Viability
Are LLM-Enhanced Graph Neural Networks Robust against Poisoning Attacks?
Score 7.0up
Higher Viability
GEAKG: Generative Executable Algorithm Knowledge Graphs
Score 7.0up
Higher Viability
Poisoning the Inner Prediction Logic of Graph Neural Networks for Clean-Label Backdoor Attacks
Score 5.0up

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