Learning from Mistakes: Can LLM Self-Recover after Misalignment?
arXiv 2606.00003•4848635207a20aae8a91bb33ef5834f7d0418df95711601fd3ad7451191c4c63
AI integrityAI literacyAI safetyEU AI ActLLM alignmentMLOpsalgorithm registersalgorithmic transparencyauditabilitybackdoorsdataset/visualizereducation accessibilitygovernancehuman-AI conformityjailbreakinglegal NLPmechanistic interpretabilitymetaversemodel self-recoverypost-market monitoringsecret loyaltiessemantic auditingsmart citiessocial influenceupdate opacity
Paper metadata
- arXiv ID
- 2606.00003
- Version
- Not specified by this published record
- Category
- Computer Science — Computers and Society (cs.CY)
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Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- 4848635207a20aae8a91bb33ef5834f7d0418df95711601fd3ad7451191c4c63
- Enrichment time
- 2026-06-02T07:23:56Z
- AI-assisted enrichment
- Yes
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