Giskard is a new protocol using tree-structured log-sized committees and MPC-based approximate median to achieve scalable confidential and Byzantine-robust aggregation in decentralized learning.
Analyzing Information Leakage of Updates to Natural Language Models , booktitle =
2 Pith papers cite this work. Polarity classification is still indexing.
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CheckMIABench converts LLMs with intermediate checkpoints into clean MIA testbeds by using pre- and post-checkpoint training data from the same distribution and evaluates published attacks on Pythia and OLMo models while releasing an open-source library.
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Giskard : Byzantine Robust and Confidential Aggregation for Large-Scale Decentralized Learning
Giskard is a new protocol using tree-structured log-sized committees and MPC-based approximate median to achieve scalable confidential and Byzantine-robust aggregation in decentralized learning.
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CheckMIABench: Firm Foundations For Membership Inference Attacks on Language Models
CheckMIABench converts LLMs with intermediate checkpoints into clean MIA testbeds by using pre- and post-checkpoint training data from the same distribution and evaluates published attacks on Pythia and OLMo models while releasing an open-source library.