5 citations · 19 across the 10 of their papers we have counts for
10 papers
Towards Optimal Multi-draft Speculative Decoding
Zhengmian Hu, Tong Zheng, Vignesh Viswanathan +5
Large Language Models (LLMs) have become an indispensable part of natural language processing tasks. However, autoregressive sampling has become an efficiency bottleneck. Multi-Dra…
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction
Yanshuo Chen, Zhengmian Hu, Wei Chen +1
\textbf{Motivation:} Predicting single-cell perturbation responses requires mapping between two unpaired single-cell data distributions. Optimal transport (OT) theory provides a pr…
A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution
Zhengmian Hu, Tong Zheng, Heng Huang
Authorship attribution aims to identify the origin or author of a document. Traditional approaches have heavily relied on manual features and fail to capture long-range correlation…
Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models
Zhengmian Hu, Heng Huang
Large language models are probabilistic models, and the process of generating content is essentially sampling from the output distribution of the language model. Existing watermark…
Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions
Yihan Wu, Ruibo Chen, Zhengmian Hu +4
Language model (LM) watermarking techniques inject a statistical signal into LM-generated content by substituting the random sampling process with pseudo-random sampling, using wat…
Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information
Zhengmian Hu, Gang Wu, Saayan Mitra +4
In recent years, Large Language Models (LLM) have emerged as pivotal tools in various applications. However, these models are susceptible to adversarial prompt attacks, where attac…
GPT-4 Vision on Medical Image Classification -- A Case Study on COVID-19 Dataset
Ruibo Chen, Tianyi Xiong, Yihan Wu +6
This technical report delves into the application of GPT-4 Vision (GPT-4V) in the nuanced realm of COVID-19 image classification, leveraging the transformative potential of in-cont…
Unbiased Watermark for Large Language Models
Zhengmian Hu, Lichang Chen, Xidong Wu +3
The recent advancements in large language models (LLMs) have sparked a growing apprehension regarding the potential misuse. One approach to mitigating this risk is to incorporate w…
Shielding the Unseen: Privacy Protection through Poisoning NeRF with Spatial Deformation
Yihan Wu, Brandon Y. Feng, Heng Huang
In this paper, we introduce an innovative method of safeguarding user privacy against the generative capabilities of Neural Radiance Fields (NeRF) models. Our novel poisoning attac…
A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models
Yihan Wu, Zhengmian Hu, Junfeng Guo +2
Watermarking techniques offer a promising way to identify machine-generated content via embedding covert information into the contents generated from language models. A challenge i…