Automating end-to-end data science pipeline with AI agents still stalls on two gaps: generating insightful, diverse visual evidence and assembling it into a coherent, professional report. We present A2P-Vis, a two-part, multi-agent pipeline that turns raw datasets into a high-quality data-visualization report. The Data Analyzer orchestrates profiling, proposes diverse visualization directions, generates and executes plotting code, filters low-quality figures with a legibility checker, and elicits candidate insights that are automatically scored for depth, correctness, specificity, depth and actionability. The Presenter then orders topics, composes chart-grounded narratives from the top-ranked insights, writes justified transitions, and revises the document for clarity and consistency, yielding a coherent, publication-ready report. Together, these agents convert raw data into curated materials (charts + vetted insights) and into a readable narrative without manual glue work. We claim that by coupling a quality-assured Analyzer with a narrative Presenter, A2P-Vis operationalizes co-analysis end-to-end, improving the real-world usefulness of automated data analysis for practitioners. For the complete dataset report, please see: https://www.visagent.org/api/output/f2a3486d-2c3b-4825-98d4-5af25a819f56.
翻译:利用智能体实现端到端数据科学流程的自动化,目前仍面临两大瓶颈:生成具有深刻见解且多样化的可视化证据,并将其组织成连贯、专业的报告。本文提出A2P-Vis,一个由两部分组成的多智能体流水线,能够将原始数据集转化为高质量的数据可视化报告。数据分析器负责统筹数据剖析、提出多样化的可视化方向、生成并执行绘图代码、通过可读性检查器筛选低质量图表,并推导候选洞察——这些洞察会自动从深度、正确性、特异性、深刻度和可操作性五个维度进行评分。随后,呈现器对主题进行排序,根据评分最高的洞察撰写基于图表的叙述,编写合理的过渡段落,并对文档进行清晰度和一致性的修订,最终生成一份连贯、可直接发表的报告。这两个智能体共同协作,将原始数据转化为经过筛选的材料(图表+已验证的洞察),再转化为可读的叙述,无需人工进行拼接工作。我们认为,通过将质量有保证的分析器与具备叙述能力的呈现器相结合,A2P-Vis实现了端到端的协同分析操作化,提升了自动化数据分析对实际应用者的现实效用。完整的数据集报告请参见:https://www.visagent.org/api/output/f2a3486d-2c3b-4825-98d4-5af25a819f56。