Academic Research Reading · 18 PAGES

ResearchStudio-Reel: Automate the Last Mile of Research from Paper to Poster, Video, and Blog

论文阅读 deck 18 页(英文)— 以 arXiv:2607.04438 的 PDF 为唯一源(首个 PDF 源示例),挂载 academic-research 方法模板,论文自身顺序:问题、相关工作、贡献、五个 skill 各一页、Table 1 原生表、散点+对照柱图分析、Figure 10 六格、成本、应用、局限、结论;19 张论文原图当证据不重绘,4 原生图 7 原生表 3 超链接,Default 路线源文件驱动生成

本作品来自 MIT 许可的 PPT Master Examples。下方展示全部 18 页;点击页面可放大浏览。

01 / 18ResearchStudio-Reel: Automate the Last Mile of Research from Paper to Poster, Video, and Blog
02 / 18The last mile of research is a separate layer, prepared in the days after acceptance, and three gaps remain open
03 / 18Prior work is organized by output type; contracts differ in editability, and VLM scores are mostly used for evaluation, not as release gates
04 / 18The answer: a native-editable workspace of five skills — one shared extractor, three editable generators, one convergence layer
05 / 18Paper2Assets reads the PDF once and emits one bundle every generator consumes verbatim; figure cleanup runs once
06 / 18Paper2Poster composes on four orthogonal axes, fills the page with a measured loop, and exports native PowerPoint shapes
07 / 18The fill loop is discrete: five verdict bands, one section edited per round, termination as a categorical fixed point
08 / 18Paper2Video plans duration before rendering, anchors narration to visible objects, and gates an editable deck plus two MP4s
09 / 18Paper2Blog writes the Chinese and English articles separately from one evidence map, then gates the Word files on layout
10 / 18Paper2Reel is a presentation surface, not a fourth summary: one alignment sidecar makes four artifacts views of one section
11 / 18Best automated system on all three aesthetic sub-criteria (3.56 vs the authors' 3.03) and on two of three information sub-criteria
12 / 18The PaperQuiz ordering nearly reverses the aesthetic ordering: denser posters answer more; the fill loop packs to a target density
13 / 18With the skill, prompt, and pipeline fixed, five configurations each produce a full page differing in figure choice, density, and accent
14 / 18A full four-artifact bundle takes about 89 minutes of stage time and 2.6M input / 276K output tokens per paper
15 / 18Three contexts span the dissemination spectrum on one pipeline: a camera-ready week, a lab's intake, a course's weekly packs
16 / 18Five failure modes recur in end-to-end runs; the system is calibrated on ML / CV / NLP venues only; quantitative evaluation covers the poster
17 / 18Supported: a native-editable, section-aligned workspace with testable gates. Open: reading-and-recall evaluation and bespoke diagrams
18 / 18Sources