{"data":{"id":"8289ffd8-db59-4b6a-ba78-03b94dc2b12d","title":"Why Empirical Risk Minimization Performs Well for Open Set Domain Adaptation: A Theoretical Analysis From Causal View","summary":"This research paper examines why classical empirical risk minimization (ERM) performs well on open set domain adaptation (OSDA), a setting with unknown target classes and shifted distributions. The authors introduce the fully informative causal invariance model (FICIM) and the partially informative causal invariance model (PICIM), and derive an OSDA theoretical bound showing ERM performs well under FICIM but poorly under PICIM. Experiments on multiple datasets validate these results, which the authors suggest may also inform training and fine-tuning of large language models (LLMs).","solution":"N/A -- no mitigation discussed in source.","labels":["research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11569816","publishedAt":"2026-06-17T13:16:25.000Z","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":"2026-06-17T13:16:25.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":null,"llmSpecific":false,"classifierConfidence":0.7,"researchCategory":"peer_reviewed","atlasIds":null}}