{"data":{"id":"b4283bb8-7fdf-42c4-9a2f-ab412c4a19b9","title":"Data-Efficient LLM Safety Alignment Guided by Interpretable Features","summary":"Researchers propose Less is Safer (LIS), a 2.4K-sample dataset for LLM safety alignment, built by selecting prompts via Sparse Autoencoder (SAE) activations and by multi-agent adversarial synthesis of harmless prompts that still trigger unnecessary refusals. On four safety and five over-refusal benchmarks, LIS outperforms much larger datasets such as TRIDENT-Core (26K), TRIDENT-Edge (19K) and WildJailbreak (262K). Ablations show that safety data alone and over-refusal data alone each fall short of optimal results.","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"https://arxiv.org/abs/2611.16183v1","publishedAt":"2026-11-12T02:15:45.000Z","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":"2026-11-12T02:15:45.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["safety"],"aiComponentTargeted":"model","llmSpecific":true,"classifierConfidence":0.95,"researchCategory":"preprint","atlasIds":null}}