Quantization Enables Private Dense Retrieval against Malicious Service Providers

arXiv:2609.36376 · cs.CR, cs.AI · Submitted 2026-09-28 · Read on arXiv

cs.CR, cs.AI

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/tremblaythibaultl/pdr-artifact

Terminology

• Quantization — 36× in this paper · explained in 12 episodes
• Embeddings — 20× in this paper · explained in 2 episodes
• Accuracy — 19× in this paper · explained in 1 episode
• RAG — 18× in this paper · explained in 3 episodes
• Verification — 10× in this paper · explained in 2 episodes
• Representation Learning — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 3× in this paper
• SIGSAC Conference on Computer and Communications Security — 2× in this paper
• Clustering — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• General Learning With Errors — 1× in this paper
• Information Leakage — 1× in this paper · explained in 2 episodes
• Quantization-Aware Training — 1× in this paper · explained in 3 episodes
• Retrieval Augmented Generation — 1× in this paper
• Retrieval Augmented Generation (RAG) — 1× in this paper · explained in 4 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes
• Verifiability — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Phi-4 Technical Report
• PPMI: Privacy-Preserving LLM Interaction with Socratic Chain-of-Thought Reasoning and Homomorphically Encrypted Vector Databases
• AnglE-optimized Text Embeddings
• Towards General Text Embeddings with Multi-stage Contrastive Learning
• 2 OLMo 2 Furious
• Qwen2.5 Technical Report
• BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
• Text Embeddings by Weakly-Supervised Contrastive Pre-training
• C-Pack: Packed Resources For General Chinese Embeddings
• Arctic-Embed 2.0: Multilingual Retrieval Without Compromise

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