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Fix research links: canonical dataset names, Paper B title and v1.0 pointer

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  1. README.md +2 -2
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@@ -37,8 +37,8 @@ Setloop helps teams design, build and operate production AI systems. Our work sp
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  Setloop Lab investigates privacy and security in distributed AI. We publish papers, datasets and reproduction artefacts so that findings can be inspected and extended.
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  - **[Privacy Failure in Split-LLM Training: The Returned Gradient Nullifies the Decoys](https://huggingface.co/papers/2609.04382)**
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- - **[Paper A reproduction package](https://huggingface.co/datasets/Setloop/llm-attacker-paper-a)** — privacy, utility and delegation feasibility in split language models.
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- - **[Paper B reproduction package](https://huggingface.co/datasets/Setloop/llm-attacker-paper-b)** — a unified red-team framework for split and distributed LLM systems.
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  ## Work with us
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  Setloop Lab investigates privacy and security in distributed AI. We publish papers, datasets and reproduction artefacts so that findings can be inspected and extended.
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  - **[Privacy Failure in Split-LLM Training: The Returned Gradient Nullifies the Decoys](https://huggingface.co/papers/2609.04382)**
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+ - **[Paper A reproduction package](https://huggingface.co/datasets/Setloop/What-Gradients-Add-to-Text-Leakage-in-Split-Language-Models-Counted-per-Token-and-per-Document)** — privacy, utility and delegation feasibility in split language models.
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+ - **[Paper B: The LLM Attacker — A Unified Red-Team Framework for Privacy Evaluation of Split and Distributed LLMs](https://huggingface.co/datasets/Setloop/The-LLM-Attacker-Unified-Red-Team-Framework-for-Privacy-Evaluation-of-Split-and-Distributed-LLMs/tree/v1.0)** — reproduction package, combined manuscript and full evidence release (v1.0).
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  ## Work with us
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