Similarity Is Not Validity: Defending LLM Semantic Caches Against Poisoning
cs.CR, cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/shentoumengxin/deletion-gain
Terminology
Sources
- Detecting Language Model Attacks with Perplexity
- Baseline Defenses for Adversarial Attacks Against Aligned Language Models
- Certifying LLM Safety against Adversarial Prompting
- Towards General Text Embeddings with Multi-stage Contrastive Learning
- LaCache: Robust Semantic Caching for LLM Serving
- GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Caching
- DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
- vCache: Verified Semantic Prompt Caching
- GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
- Text Embeddings by Weakly-Supervised Contrastive Pre-training
- Qwen3 Technical Report
- Geometry-Guided Adversarial Prompt Detection via Curvature and Local Intrinsic Dimension
- From Similarity to Vulnerability: Key Collision Attack on LLM Semantic Caching
- Universal and Transferable Adversarial Attacks on Aligned Language Models
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