{"data":{"id":"bf82024c-d91c-4180-922a-395e3895ffdc","title":"Evaluating Large Language Models on Named Entity Recognition","summary":"Researchers evaluate twenty-eight representative LLMs on thirteen named entity recognition (NER) datasets across five domains, with parameter counts from 3 billion to 175 billion. They assess supervised fine-tuning, parameter scale, hallucinations and prompt designs using an LLM-based NER framework (LLM-NER) with a Recognition phase and a Check phase. The study finds that fine-tuning improves instruction following, performance rises with parameter scale, hallucinations appear in all evaluated models, and all models are sensitive to prompt design.","solution":"Guiding LLMs to check their outputs, via the Check phase of LLM-NER, is described as a feasible way to alleviate hallucinations.","labels":["research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11474527","publishedAt":"2026-04-03T13:16:51.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"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":"2026-04-03T13:16:51.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":null,"llmSpecific":true,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}