Enforcing Trust Accountability with Backward Propagation
2026-06-09T08:52:20Z•d7f0ef409d2fb128f1bd17f9acd7c8de23b9415fdb46c2c3849a50e09bd5eade
ALCMeansDeepWalkGraph Foundation ModelsRepuLinkSPINSybil/misinfo mitigationagent-based modelingbackward propagationcold-startcommunity detectiondecentralized swarm controldual-use riskedge/low-power agentsendorsement accountabilitygraph learningnetwork dynamicspersonalization/highlighting leakageprivacy/deanonymizationsemantic shiftslang/entity detectionsuper-spreader identificationtelehealth modelingtensor networkstrust and reputationts-net
What happened
This collection of recent arXiv papers spans trust/reputation systems, community and graph learning, decentralized swarm control, semantic shift detection, and socio-technical analyses (telehealth, sustainability, software labor). Key technical contributions with security relevance include RepuLink — a two-layer reputation model that enforces endorser accountability via backward endorsement penalty/reward propagation (affects trust bootstrapping and mitigation of malicious actors but could be gamed or cause cascading penalties); SPIN — a low-power, tensorized decentralized swarm-control policy
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- d7f0ef409d2fb128f1bd17f9acd7c8de23b9415fdb46c2c3849a50e09bd5eade
- Enrichment time
- 2026-06-09T08:52:20Z
- AI-assisted enrichment
- Yes
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