Yeseul E. Chang
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126
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Crypto×1AI×1Info Retrieval×1
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2026
Retrieval Augmented Classification for Confidential Documents
The paper proposes Retrieval Augmented Classification (RAC) as a robust, low-leakage method for classifying confidential documents, demonstrating that RAC outperforms supervised fine-tuning (FT) particularly when dealing with class imbalance and real-world data constraints.
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cs.CRcs.AIcs.IRRecentApr 9, 2026
Retrieval Augmented Classification for Confidential Documents
Yeseul E. Chang, Rahul Kailasa, Simon Shim, Byunghoon Oh +1 more
The paper proposes Retrieval Augmented Classification (RAC) as a robust, low-leakage method for classifying confidential documents, demonstrating that RAC outperforms supervised fine-tuning (FT) parti…
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