4 citations · 6 across the 9 of their papers we have counts for
9 papers
MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models
Leyi Pan, Sheng Guan, Zheyu Fu +9
We introduce MarkDiffusion, an open-source Python toolkit for generative watermarking of latent diffusion models. It comprises three key components: a unified implementation framew…
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?
Leyi Pan, Aiwei Liu, Shiyu Huang +5
The radioactive nature of Large Language Model (LLM) watermarking enables the detection of watermarks inherited by student models when trained on the outputs of watermarked teacher…
WaterSeeker: Pioneering Efficient Detection of Watermarked Segments in Large Documents
Leyi Pan, Aiwei Liu, Yijian Lu +6
Watermarking algorithms for large language models (LLMs) have attained high accuracy in detecting LLM-generated text. However, existing methods primarily focus on distinguishing fu…
Astra: Efficient Transformer Architecture and Contrastive Dynamics Learning for Embodied Instruction Following
Yueen Ma, Dafeng Chi, Shiguang Wu +3
Vision-language-action models have gained significant attention for their ability to model multimodal sequences in embodied instruction following tasks. However, most existing mode…
Entropy-Based Decoding for Retrieval-Augmented Large Language Models
Zexuan Qiu, Zijing Ou, Bin Wu +3
Augmenting Large Language Models (LLMs) with retrieved external knowledge has proven effective for improving the factual accuracy of generated responses. Despite their success, ret…
MarkLLM: An Open-Source Toolkit for LLM Watermarking
Leyi Pan, Aiwei Liu, Zhiwei He +9
LLM watermarking, which embeds imperceptible yet algorithmically detectable signals in model outputs to identify LLM-generated text, has become crucial in mitigating the potential…
An Entropy-based Text Watermarking Detection Method
Yijian Lu, Aiwei Liu, Dianzhi Yu +2
Text watermarking algorithms for large language models (LLMs) can effectively identify machine-generated texts by embedding and detecting hidden features in the text. Although the…
CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models
Zexuan Qiu, Jingjing Li, Shijue Huang +3
Developing Large Language Models (LLMs) with robust long-context capabilities has been the recent research focus, resulting in the emergence of long-context LLMs proficient in Chin…
A Survey of Text Watermarking in the Era of Large Language Models
Aiwei Liu, Leyi Pan, Yijian Lu +7
Text watermarking algorithms are crucial for protecting the copyright of textual content. Historically, their capabilities and application scenarios were limited. However, recent a…