DeTox-Fed uses federated graph neural networks on local conversation graphs to detect toxic discussions in the Fediverse while keeping all raw data and labels on individual instances.
Inductive Representation Learning on Large Graphs , volume =
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
EHRAG constructs structural hyperedges from sentence co-occurrence and semantic hyperedges from entity embedding clusters, then applies hybrid diffusion plus topic-aware PPR to retrieve top-k documents, outperforming baselines on four datasets with linear indexing cost and zero token overhead.
citing papers explorer
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DeTox-Fed: Detecting Toxic Conversations in the Fediverse with Federated Graph Neural Networks
DeTox-Fed uses federated graph neural networks on local conversation graphs to detect toxic discussions in the Fediverse while keeping all raw data and labels on individual instances.
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EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval
EHRAG constructs structural hyperedges from sentence co-occurrence and semantic hyperedges from entity embedding clusters, then applies hybrid diffusion plus topic-aware PPR to retrieve top-k documents, outperforming baselines on four datasets with linear indexing cost and zero token overhead.