To mitigate the potential misuse of large language models (LLMs), recent research has developed watermarking algorithms, which restrict the generation process to leave an invisible trace for watermark detection. Due to the two-stage nature of the task, most studies evaluate the generation and detection separately, thereby presenting a challenge in unbiased, thorough, and applicable evaluations. In this paper, we introduce WaterBench, the first comprehensive benchmark for LLM watermarks, in which we design three crucial factors: (1) For \textbf{benchmarking procedure}, to ensure an apples-to-apples comparison, we first adjust each watermarking method's hyper-parameter to reach the same watermarking strength, then jointly evaluate their generation and detection performance. (2) For \textbf{task selection}, we diversify the input and output length to form a five-category taxonomy, covering $9$ tasks. (3) For \textbf{evaluation metric}, we adopt the GPT4-Judge for automatically evaluating the decline of instruction-following abilities after watermarking. We evaluate $4$ open-source watermarks on $2$ LLMs under $2$ watermarking strengths and observe the common struggles for current methods on maintaining the generation quality. The code and data are available at \url{https://github.com/THU-KEG/WaterBench}.

BENGALURU: Artificial Intelligence (AI) is taking a centre stage in operations of enterprises defying talks of hype around it, according to research reports released by Accenture and Infosys. These research reports, which covered more than 2000 business leaders across different global markets including India, state that majority of businesses globally have started seeing results of AI. Nearly 3 out of 4 businesses are actively deploying AI-based technologies and it has disrupted the way they did business before, said Infosys citing its study "Leadership in the Age of AI". AI implementation has yielded business results and would soon impact overall revenue growth of large businesses. "India, the United States and China led geographies with the most respondents saying that their organization has realized direct, tangible results from deploying AI technologies with 75 percent, 71 percent and 61 percent respectively," noted Infosys in its report.