Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation

arXiv:2604.06831 · cs.CR, cs.AI · Submitted 2026-04-08 · Read on arXiv

cs.CR, cs.AI

Submitted: 2026-04-08

Updated: 2026-04-08

Journal ref: ACL 2026

DOI: 10.18653/v1/2026.acl-long.1191

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Embeddings — 63× in this paper · explained in 2 episodes
• Adaptation — 29× in this paper · explained in 1 episode
• Fine-Tuning — 24× in this paper · explained in 5 episodes
• Alignment — 17× in this paper · explained in 1 episode
• Domain Adaptation — 15× in this paper · explained in 5 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Robustness — 8× in this paper · explained in 5 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Differential Privacy — 5× in this paper · explained in 4 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Differentially Private — 4× in this paper · explained in 3 episodes
• Privacy-Preserving Fine-Tuning — 4× in this paper
• Ablation study — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Computational overhead — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Federated Learning — 2× in this paper · explained in 14 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Scaffolding — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Communication Overhead — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Multimodal Inputs — 1× in this paper · explained in 2 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• GPT-4 Technical Report
• Casper: Prompt Sanitization for Protecting User Privacy in Web-Based Large Language Models
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• LoRA: Low-Rank Adaptation of Large Language Models
• Lawyer LLaMA Technical Report
• Sentence Embedding Leaks More Information than You Expect: Generative Embedding Inversion Attack to Recover the Whole Sentence
• Split-and-Denoise: Protect large language model inference with local differential privacy
• Evaluating Privacy Leakage in Split Learning
• Differentially Private Fine-tuning of Language Models
• A Split-and-Privatize Framework for Large Language Model Fine-Tuning
• The Fire Thief Is Also the Keeper: Balancing Usability and Privacy in Prompts
• Universal Zero-shot Embedding Inversion

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