DeepSlide: From Artifacts to Presentation Delivery
DeepSlide is a new multi-agent system designed to enhance the presentation delivery process. It focuses on improving narrative flow, pacing precision, and slide-script synergy while maintaining high artifact quality. The system integrates various components to support the full presentation preparation process, from planning to rehearsal.
- ▪DeepSlide optimizes both the artifact quality and the delivery process of presentations.
- ▪The system includes features like a controllable logical-chain planner and attention augmentation.
- ▪DeepSlide has shown significant improvements in delivery metrics across diverse audience profiles.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.15202 |
| Publication time | Mon, 18 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-18T04:04:54.418Z |
| Last seen | 2026-05-18T04:04:54.418Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | UzbzYzTZyakz |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.15202 (cs) [Submitted on 1 Apr 2026] Title:DeepSlide: From Artifacts to Presentation Delivery Authors:Ming Yang, Zhiwei Zhang, Jiahang Li, Haoseng Liu, Yuzheng Cai, Weiguo Zheng View a PDF of the paper titled DeepSlide: From Artifacts to Presentation Delivery, by Ming Yang and 5 other authors View PDF HTML (experimental) Abstract:Presentations are a primary medium for scholarly communication, yet most AI slide generators optimize the artifact (a visually plausible deck) while under-optimizing the delivery process (pacing, narrative, and presentation preparation).
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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