Stable-GFlowNet improves training stability and attack diversity in LLM red-teaming by eliminating Z estimation via contrastive trajectory balance while preserving GFN optimality.
Journal of statistical mechanics: theory and experiment , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
The paper examines denial-of-service risks to multi-round transaction simulation arising from inter-transaction dependencies in smart-contract state.
CluProp reframes varied-density clustering as deterministic label propagation over neighborhood graphs for improved robustness and scalability.
citing papers explorer
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Stable-GFlowNet: Toward Diverse and Robust LLM Red-Teaming via Contrastive Trajectory Balance
Stable-GFlowNet improves training stability and attack diversity in LLM red-teaming by eliminating Z estimation via contrastive trajectory balance while preserving GFN optimality.
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Position Paper: Denial-of-Service against Multi-Round Transaction Simulation
The paper examines denial-of-service risks to multi-round transaction simulation arising from inter-transaction dependencies in smart-contract state.
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Towards Robust and Scalable Density-based Clustering via Graph Propagation
CluProp reframes varied-density clustering as deterministic label propagation over neighborhood graphs for improved robustness and scalability.