Learning from Mistakes: Can LLM Self-Recover after Misalignment?

2026-06-02T07:23:56Z4848635207a20aae8a91bb33ef5834f7d0418df95711601fd3ad7451191c4c63
AI integrityAI literacyAI safetyEU AI ActLLM alignmentMLOpsalgorithm registersalgorithmic transparencyauditabilitybackdoorsdataset/visualizereducation accessibilitygovernancehuman-AI conformityjailbreakinglegal NLPmechanistic interpretabilitymetaversemodel self-recoverypost-market monitoringsecret loyaltiessemantic auditingsmart citiessocial influenceupdate opacity

What happened

Collection of recent AI/CS policy and safety papers (arXiv 2606.x) covering LLM alignment resilience, algorithmic influence on human moral decisions, governance and transparency tools, and integrity risks. Key contributions include: a methodology and dataset for measuring LLM self-recovery after jailbreaking; experimental evidence that AI reasoning can produce conformity effects on moral judgments; a multimodal NLP pipeline for semantic auditing of Greek legislation (including anti-scraping acquisition); a systematic review of metaverse applications for smart cities; a call to make mechanistic

Why it matters

A reviewed impact interpretation has not been published for this record.

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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