LLM Security

Large Language Models are Easily Confused: A Quantitative Metric, Security Implications and Typological Analysis
Language Confusion is a phenomenon where Large Language Models (LLMs) generate text that is neither in the desired language, nor in a …
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Against All Odds: Overcoming Typology, Script, and Language Confusion in Multilingual Embedding Inversion Attacks
Large Language Models (LLMs) are susceptible to malicious influence by cyber attackers through intrusions such as adversarial, …
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Text Embedding Inversion Security for Multilingual Language Models
Textual data is often represented as real-numbered embeddings in NLP, particularly with the popularity of large language models (LLMs) …
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