Hugging Face Daily Papers：代理计算机图形学的进展
Advances in Agentic Computer Graphics
Hugging Face Daily Papers发布了一份关于由大语言模型驱动的代理计算机图形学的报告，提出了统一分类法和文献系统，分析了人机协作和长期规划的趋势与挑战。报告介绍了用于表征不同计算机图形任务中代理系统的统一分类法，并开发了可协助研究人员大规模分析现有及新发表论文的代理文献系统。
Published on Nov 1
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Abstract
This report proposes a unified taxonomy and literature system for agentic computer graphics driven by large language models, analyzing trends and open challenges in human-agent collaboration and long-horizon planning.
Computer graphics is built on code. Large language model (LLM) agents can now generate graphics code and iteratively refine it through various feedback. This capability opens the door to a potentially new paradigm of computer graphics, with graphics algorithms increasingly built around agentic systems to automate progressively complex tasks. Over the past years, research on agentic graphics has expanded rapidly across a diverse range of tasks. This rapid growth makes it increasingly difficult for manual literature reviews to keep pace with new developments. At the same time, similar ideas are often described using different terminology across these tasks, further complicating efforts to develop a systematic understanding of the field. In this report, we address these challenges through two contributions. First, we introduce a unified taxonomy for characterizing agentic systems across diverse computer graphics tasks. Second, we develop an agentic literature system that can assist human researchers in analyzing existing and newly published papers at scale. Building on these contributions, we analyze emerging research trends and discuss open challenges in coordinating agents and tools across graphics tasks, designing interfaces and representations for human-agent collaboration, sustaining long-horizon planning and refinement, and reliably evaluating interactive graphics systems.
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来源: Hugging Face Daily Papers · huggingface.co