Personal llm agents: Insights and survey about the capability, efficiency and security
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have
been one of the key technologies that researchers and engineers have focused on, aiming …
been one of the key technologies that researchers and engineers have focused on, aiming …
Grounding foundation models through federated transfer learning: A general framework
Foundation Models (FMs) such as GPT-4 encoded with vast knowledge and powerful
emergent abilities have achieved remarkable success in various natural language …
emergent abilities have achieved remarkable success in various natural language …
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) and Embeddings as a Service (EaaS) …
popularity of large language models (LLMs) and Embeddings as a Service (EaaS) …
Cogenesis: A framework collaborating large and small language models for secure context-aware instruction following
With the advancement of language models (LMs), their exposure to private data is
increasingly inevitable, and their deployment (especially for smaller ones) on personal …
increasingly inevitable, and their deployment (especially for smaller ones) on personal …
Privacy preserving prompt engineering: A survey
Pre-trained language models (PLMs) have demonstrated significant proficiency in solving a
wide range of general natural language processing (NLP) tasks. Researchers have …
wide range of general natural language processing (NLP) tasks. Researchers have …
Privinfer: Privacy-preserving inference for black-box large language model
Large language models (LLMs), such as ChatGPT, have simplified text generation tasks, yet
their inherent privacy risks are increasingly garnering attention. While differential privacy …
their inherent privacy risks are increasingly garnering attention. While differential privacy …
Text Embedding Inversion Attacks on Multilingual Language Models
Representing textual information as real-numbered embeddings has become the norm in
NLP. Moreover, with the rise of public interest in large language models (LLMs) …
NLP. Moreover, with the rise of public interest in large language models (LLMs) …
Differentially Private Multimodal Laplacian Dropout (DP-MLD) for EEG Representative Learning
Recently, multimodal electroencephalogram (EEG) learning has shown great promise in
disease detection. At the same time, ensuring privacy in clinical studies has become …
disease detection. At the same time, ensuring privacy in clinical studies has become …
Just Rewrite It Again: A Post-Processing Method for Enhanced Semantic Similarity and Privacy Preservation of Differentially Private Rewritten Text
S Meisenbacher, F Matthes - … of the 19th International Conference on …, 2024 - dl.acm.org
The study of Differential Privacy (DP) in Natural Language Processing often views the task of
text privatization as a rewriting task, in which sensitive input texts are rewritten to hide …
text privatization as a rewriting task, in which sensitive input texts are rewritten to hide …
Protecting Privacy in Classifiers by Token Manipulation
Using language models as a remote service entails sending private information to an
untrusted provider. In addition, potential eavesdroppers can intercept the messages, thereby …
untrusted provider. In addition, potential eavesdroppers can intercept the messages, thereby …