{"data":{"id":"ac3aebc8-75db-47c4-8ff1-3b2536af790c","title":"A unified multi-domain framework for hallucination detection and reliability evaluation in large language models","summary":"Researchers introduce MDH-Bench, a benchmark of 400 adversarial yet naturalistic prompts across eight reliability categories, and a Unified Multi-Domain Reliability Evaluation Framework that combines accuracy, hallucination rate, contradiction rate and safety indicators into a composite R-Score. Across four LLMs (GPT-5.2, Claude Sonnet 4, Gemini 2.5 Pro, DeepSeek V3.1), GPT-5.2 scored highest (80.10% accuracy, R-Score 0.8715), while DeepSeek V3.1 scored lowest (63.60% accuracy, 37.55% hallucination rate, R-Score 0.7074).","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"https://doi.org/10.1038/s41598-026-76014-w","publishedAt":"2026-10-15T00:00:00.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":["OpenAI","Anthropic","Google"],"affectedVendorsRaw":["GPT-5.2","Claude Sonnet 4","Gemini 2.5 Pro","DeepSeek V3.1"],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-10-15T00:00:00.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","safety"],"aiComponentTargeted":"model","llmSpecific":true,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}