AIAISci
中文
paperAI

Data protection in the era of large language models: challenges and opportunities

Data protection in the era of large language models: challenges and opportunities

publishedDate Venue AI and Ethics

Source-permitted summary

Data protection in the era of large language models: challenges and opportunities

SourceSpringer Science and Business Media LLC

Verified by AISci

Public source attached

Source status for this paper in the current AISci reviewed snapshot.

Primary source
Springer Science and Business Media LLC
Correction status
none
Evidence coverage
1 sources / 1 publishers
Last metadata check
Jul 19, 2026
DOI: 10.1007/s43681-026-01223-y
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AI Reading Notes

Core signal

Structured notes generated from source-linked AISci metadata. Treat them as a reading aid, not a substitute for the paper.

Core signal
Data protection in the era of large language models: challenges and opportunities
Field context
Foundation Models and Agents
People and labs
Not stated in the reviewed source.
Why it matters
Recent source-backed research output for AISci Stage A browsing.
Limits to check
AISci rank score does not assess scientific quality or citation impact.

Publication facts

External IDs

Author order

No reviewed author edge is attached to this output.

Organizations

No source-confirmed author affiliation is attached.

Related events

Data protection in the era of large language models: challenges and opportunities

Topics

Foundation Models and Agents

Relationship evidence

Timeline

  2. paperData protection in the era of large language models: challenges and opportunities
    SourceSpringer Science and Business Media LLC