Privacy in large language models: Attacks, defenses and future directions
The advancement of large language models (LLMs) has significantly enhanced the ability to
effectively tackle various downstream NLP tasks and unify these tasks into generative …
effectively tackle various downstream NLP tasks and unify these tasks into generative …
Federated large language model: A position paper
Large scale language models (LLM) have received significant attention and found diverse
applications across various domains, but their development encounters challenges in real …
applications across various domains, but their development encounters challenges in real …
Generating valid and natural adversarial examples with large language models
Deep learning-based natural language processing (NLP) models, particularly pre-trained
language models (PLMs), have been revealed to be vulnerable to adversarial attacks …
language models (PLMs), have been revealed to be vulnerable to adversarial attacks …
Integration of large language models and federated learning
As the parameter size of large language models (LLMs) continues to expand, there is an
urgent need to address the scarcity of high-quality data. In response, existing research has …
urgent need to address the scarcity of high-quality data. In response, existing research has …
Multi-granular Adversarial Attacks against Black-box Neural Ranking Models
Adversarial ranking attacks have gained increasing attention due to their success in probing
vulnerabilities, and, hence, enhancing the robustness, of neural ranking models …
vulnerabilities, and, hence, enhancing the robustness, of neural ranking models …
Breaking agents: Compromising autonomous llm agents through malfunction amplification
Recently, autonomous agents built on large language models (LLMs) have experienced
significant development and are being deployed in real-world applications. These agents …
significant development and are being deployed in real-world applications. These agents …
Exposing the Achilles' heel of textual hate speech classifiers using indistinguishable adversarial examples
The accessibility of online hate speech has increased significantly, making it crucial for
social-media companies to prioritize efforts to curb its spread. Although deep learning …
social-media companies to prioritize efforts to curb its spread. Although deep learning …
Following Clues, Approaching the Truth: Explainable Micro-Video Rumor Detection via Chain-of-Thought Reasoning
R Hong, J Lang, J Xu, Z Cheng, T Zhong… - THE WEB CONFERENCE … - openreview.net
The rapid spread of rumor content on online micro-video platforms poses significant threats
to public health and safety. However, existing Micro-Video Rumor Detection (MVRD) …
to public health and safety. However, existing Micro-Video Rumor Detection (MVRD) …