{"data":{"id":"4100a8fb-e5cc-4ecd-b3d4-7b92d65e3521","title":"Alignment of Diffusion Models: Fundamentals, Challenges, and Future","summary":"This is an academic survey paper published in ACM Computing Surveys that examines alignment of diffusion models (AI systems trained to generate images or other content by gradually removing noise from random data). The paper covers fundamental concepts, current challenges in making these models behave as intended, and directions for future research in this area.","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"https://dl.acm.org/doi/abs/10.1145/3796982?af=R","publishedAt":"2026-03-16T21:11:52.659Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["safety"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}