9 papers
MultiGhostBench: A Multilingual Benchmark for Long-Form LLM-Generated Text Attribution under Distribution Shifts
Matteo Greco, Anudeex Shetty, Andrea Tagarelli +1
While existing work on LLM authorship attribution (AA) has made progress, available benchmarks remain limited, often focusing on English, controlled settings, or relatively outdate…
Who Wrote the Book? Detecting and Attributing LLM Ghostwriters
Anudeex Shetty, Qiongkai Xu, Olga Ohrimenko +1
In this paper, we introduce GhostWriteBench, a dataset for LLM authorship attribution. It comprises long-form texts (50K+ words per book) generated by frontier LLMs, and is designe…
In Vino Veritas and Vulnerabilities: Examining LLM Safety via Drunk Language Inducement
Anudeex Shetty, Aditya Joshi, Salil S. Kanhere
Humans are susceptible to undesirable behaviours and privacy leaks under the influence of alcohol. This paper investigates drunk language, i.e., text written under the influence of…
VISPA: Pluralistic Alignment via Automatic Value Selection and Activation
Shenyan Zheng, Jiayou Zhong, Anudeex Shetty +3
As large language models are increasingly used in high-stakes domains, it is essential that their outputs reflect not average} human preference, rather range of varying perspective…
Watermarks for Embeddings-as-a-Service Large Language Models
Anudeex Shetty
Large Language Models (LLMs) have demonstrated exceptional capabilities in natural language understanding and generation. Based on these LLMs, businesses have started to provide Em…
Pluralistic Alignment for Healthcare: A Role-Driven Framework
Jiayou Zhong, Anudeex Shetty, Chao Jia +2
As large language models are increasingly deployed in sensitive domains such as healthcare, ensuring their outputs reflect the diverse values and perspectives held across populatio…
VITAL: A New Dataset for Benchmarking Pluralistic Alignment in Healthcare
Anudeex Shetty, Amin Beheshti, Mark Dras +1
Alignment techniques have become central to ensuring that Large Language Models (LLMs) generate outputs consistent with human values. However, existing alignment paradigms often mo…
WET: Overcoming Paraphrasing Vulnerabilities in Embeddings-as-a-Service with Linear Transformation Watermarks
Anudeex Shetty, Qiongkai Xu, Jey Han Lau
Embeddings-as-a-Service (EaaS) is a service offered by large language model (LLM) developers to supply embeddings generated by LLMs. Previous research suggests that EaaS is prone t…
WARDEN: Multi-Directional Backdoor Watermarks for Embedding-as-a-Service Copyright Protection
Anudeex Shetty, Yue Teng, Ke He +1
Embedding as a Service (EaaS) has become a widely adopted solution, which offers feature extraction capabilities for addressing various downstream tasks in Natural Language Process…