{"data":{"id":"a22ff10c-2495-4c66-b985-362ff6333c4a","title":"Language Guidance for Supervised Vision Training: An Empirical Study of Generalization","summary":"This empirical study tests whether pretrained language models can serve as lightweight auxiliary supervision for supervised vision training, without paired image-text data, prompt engineering, or contrastive objectives. The authors evaluate Explicit Language Guidance (ExLG) and Implicit Language Guidance (ImLG) across six generalization regimes, including out-of-distribution, shortcut resistance, texture and shape bias, adversarial robustness, and continual learning. Explicit guidance helps in-distribution, low-data, and continual-learning retention, while implicit guidance helps more in shortcut-sensitive and strongly adversarial settings.","solution":"N/A -- no mitigation discussed in source.","labels":["research"],"sourceUrl":"https://arxiv.org/abs/2610.27208v1","publishedAt":"2026-10-19T19:43:04.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["pretrained language models"],"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":"2026-10-19T19:43:04.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.6,"researchCategory":"preprint","atlasIds":null}}