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News/Combating Data Laundering in LLM Training
arxiv
PublishedJune 17, 2026 at 4:00 AM
—neutral

Combating Data Laundering in LLM Training

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2604.01904v3 Announce Type: replace-cross Abstract: Post-hoc unauthorized-training data detection for large language models (LLMs) typically assumes a query-with-originals regime: rights holders query a target LLM with raw proprietary data and assess whether the model assigns them stronger mem

Models mentioned
01
  • 01meta-llama logo
    Llama-2
    meta-llama/Llama-2
Related
01
  • arxivJun 3
    Experience-Driven Dynamic Exits for LLMs with Reinforcement Learning
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Discussion
Mentioned models
03
  • 01
    Llama-2
    meta-llama/Llama-2
  • 02
    Pythia
  • 03
    Falcon
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#data-laundering#detection#security#language-models

No replies yet. Be first.

Mentioned models
03
  • 01
    Llama-2
    meta-llama/Llama-2
  • 02
    Pythia
  • 03
    Falcon
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#data-laundering#detection#security#language-models

Related coverage

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