Algorithmic Trust and Compliance: Benchmarking Brand Notability for UK iGaming Entities in Generative Search Engines

2026-03-16T08:52:19Z668d3dae92accd64fde241bf90e5fd1124dd57e3fe6eb479a911ceb76fd8a5c9
CTR-predictionFinQAGEOLLM-augmentationRAGUKGCagentic-systemsalgorithmic-trustcontextualizationde-duplicationdeferred-interactionfeature-interactiongenerative-retrievalgenerative-searchgraph-neural-networkshierarchical-reasoninghuman-agent-collaborationiGamingknowledge-distillationmiscitation-detectionmulti-step-reasoningmultimodal-recommendationresearch-contextingtable-retrievalvision-language-models

What happened

Collection of recent IR/LLM papers covering: (1) Algorithmic Trust and Generative Engine Optimization (GEO) for UK iGaming — shows generative search engines overwhelmingly prefer earned third-party authoritative sources over brand-owned content and that structured compliance signals (e.g., UKGC) act as authority multipliers for LLMs; (2) LAGMiD — an LLM-augmented graph-learning miscitation detector using chain-of-thought evidence tracing and GNN distillation to cut inference cost while improving miscitation detection; (3) ReasonGR — improves multi-step semantic/numerical reasoning in generativ

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_ir
Record identifier
668d3dae92accd64fde241bf90e5fd1124dd57e3fe6eb479a911ceb76fd8a5c9
Enrichment time
2026-03-16T08:52:19Z
AI-assisted enrichment
Yes

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