mlsanityData to 14 Oct 2026

Talk to Your Slides: High-Efficiency Slide Editing via Language-Driven Structured Data Manipulation

arXiv 2505.11604 ↗First posted 16 May 2025cs.CLcited by 11

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Abstract (arXiv)

Editing presentation slides is a frequent yet tedious task, ranging from creative layout design to repetitive text maintenance. While recent GUI-based agents powered by Multimodal LLMs (MLLMs) excel at tasks requiring visual perception, such as spatial layout adjustments, they often incur high computational costs and latency when handling structured, text-centric, or batch processing tasks. In this paper, we propose Talk-to-Your-Slides, a high-efficiency slide editing agent that operates via language-driven structured data manipulation rather than relying on the image modality. By leveraging the underlying object model instead of screen pixels, our approach ensures precise content modification while preserving style fidelity, addressing the limitations of OCR-based visual agents. Our system features a hierarchical architecture that effectively bridges high-level user instructions with low-level execution codes. Experiments demonstrate that for text-centric and formatting tasks, our method enables 34% faster processing, achieves 34% better instruction fidelity, and operates at an 87% lower cost compared to GUI-based baselines. Furthermore, we introduce TSBench, a human-verified benchmark dataset comprising 379 instructions, including a Hard subset designed to evaluate robustness against complex and visually dependent queries. Our code and benchmark are available at https://github.com/KyuDan1/Talk-to-Your-Slides.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 24 of its 45 references that are in the map. First posted on arXiv 16 May 2025.

Builds on

24 of 45 references.

References · 24

  1. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,276
  2. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
  3. 2022A Survey on In-context Learningcited by 721
  4. 2024A Survey on Large Language Models for Code Generationcited by 658
  5. 2024UFO: A UI-Focused Agent for Windows OS Interactioncited by 148
  6. 2024Does Prompt Formatting Have Any Impact on LLM Performance?cited by 141
  7. 2022Large Language Models Meet NL2Code: A Surveycited by 138
  8. 2024Controllable Preference Optimization: Toward Controllable Multi-Objective Alignmentcited by 107
  9. 2022Natural Language to Code Generation in Interactive Data Science Notebookscited by 87
  10. 2025PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slidescited by 86
  11. 2023AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZcited by 79
  12. 2024If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agentscited by 79
12 more
  1. 2023How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representationscited by 75
  2. 2025AutoPresent: Designing Structured Visuals from Scratchcited by 68
  3. 2025Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineeringcited by 67
  4. 2023TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usagecited by 55
  5. 2025Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMscited by 47
  6. 2024Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programmingcited by 35
  7. 2023PPTC Benchmark: Evaluating Large Language Models for PowerPoint Task Completioncited by 30
  8. 2024Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMscited by 20
  9. 2024Enhancing Code Generation Performance of Smaller Models by Distilling the Reasoning Ability of LLMscited by 17
  10. 2025A Survey on Large Language Models for Automated Planningcited by 17
  11. 2024PPTC-R benchmark: Towards Evaluating the Robustness of Large Language Models for PowerPoint Task Completioncited by 9
  12. 2025Skill Discovery for Software Scripting Automation via Offline Simulations with LLMscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 10.

11 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026SLIDEFORGE: An LLM Agent for Controllable Editing of Slides as Structured Artifacts
  2. 2026EditPPT: Faithful Long-Deck Slide Editing via Structured Tool-Using Multi-Agent with Dual-Modal Validators
  3. 2026Design First, Code Later: Aesthetically Pleasing Template-Free Slides Generation
  4. 2024Instruction-Guided Editing Controls for Images and Multimedia: A Survey in LLM era
  5. 2026PPTBench: Can Coding Agents Reconstruct the Visual World through Structured, Editable Slides
  6. 2026PPT-Eval: A Benchmark for Computer-Use Agents on PowerPoint Tasks
  7. 2025SlideCoder: Layout-aware RAG-enhanced Hierarchical Slide Generation from Design
  8. 2025SlideBot: A Multi-Agent Framework for Generating Informative, Reliable, Multi-Modal Presentations