LLM (Large Language Model) 的滥用可能导致许多问题,这可以通过给 LLM 输出添加水印来缓解。文章作者提出了一种巧妙的添加水印的方法,在这种方法中作者随机选取一个 green tokens 集,并鼓励模型输出从该集合中选取 token,从而小成本地、隐式地为文本添加水印。 同时在该框架内部,检测水印的方法也不需要提前获得 LLM...
作者提出了一种巧妙的方法，通过随机选取一个“绿色”token集合，鼓励模型输出来自该集合的token，实现低成本、隐式的文本水印。在框架内部，检测水印的方法无需提前获取LLM的API或模型参数，基于统计方法即可分析水印的存在。
实验用的OPT-1.3B,测试对水印的攻击时用了T5-Large,总体感觉不算很典型的LLM,但也能说明不少问题了。
PaperLink A watermark for large language models. On the Reliability of Watermarks for Large Language Models A Private Watermark for Large Language Models Distillation-Resistant Watermarking for Model Protection in NLP Watermarking Pre-trained Language Models with Backdooring ...
Optimized transformers code for inference usingFlash AttentionandPaged Attentionon the most popular architectures Quantization with : bitsandbytes GPT-Q EETQ AWQ Safetensorsweight loading Watermarking withA Watermark for Large Language Models Logits warper (temperature scaling, top-p, top-k, repetition...
Except for this watermark, it is identical to the accepted version; the final published version of the proceedings is available on IEEE Xplore. A Vision Check-up for Language Models Pratyusha Sharma* 1 Tamar Rott Shaham* 1 Manel Baradad1 Stephanie Fu† 2 Adria´n Rodr´ıguez-Mun...
2.1. Large Language Models (LLMs) Large Language Models (LLMs) [18] represents an evolution from language models. Initially, language models were statistical in nature and laid the groundwork for computational linguistics. The advent of transformers has significantly increased their scale. This expan...
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Paper tables with annotated results for CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code
Large Language Models (LLMs) have achieved remarkable progress in code generation. It now becomes crucial to identify whether the code is AI-generated and to determine the specific model used, particularly for purposes such as protecting Intellectual Property (IP) in industry and preventing cheating...