mlsanityData to 14 Oct 2026

Multimedia and Visual Analytics in the Agentic Era

arXiv 2504.06138 ↗First posted 8 Apr 2025cs.MM cs.AI cs.HCcited by 1

On the map: LLM agents and tool use → Multimodal and embodied agents

Abstract (arXiv)

Professional users need tools to help them gain actionable insights from large multimedia collections. Foundation models and AI agents have rapidly changed the playing field, and improving their accuracy, trustworthiness, and reasoning capabilities are active topics in the computer vision, machine learning, and multimedia communities. Most current research focuses on benchmark driven algorithmic improvements. The multimedia community is the place to go beyond algorithms and consider complete multimedia analytics systems that support professional users in their complex tasks and achieve a true teaming of humans and AI. Supporting users with machine learning and visualizations has been studied for decades in the visual analytics field. In this paper, we propose a framework to bring multimedia and visual analytics together and indicate how it could impact current and new multimedia analytics solutions. Additional information can be found at https://staff.fnwi.uva.nl/m.worring/analytics-model.html

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 35 of its 90 references that are in the map. First posted on arXiv 8 Apr 2025.

Builds on

35 of 90 references.

References · 35

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23 more
  1. 2023Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmarkcited by 143
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Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AIcited by 42

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  3. 2024Reframe Anything: LLM Agent for Open World Video Reframing
  4. 2026VACP: Visual Analytics Context Protocol
  5. 2026WidgetVA: A Widget-Centric Framework and Benchmark for Agentic Visual Analytics
  6. 2026LensWalk: Agentic Video Understanding by Planning How You See in Videos
  7. 2026Human-Data Interaction, Exploration, and Visualization in the AI Era: Challenges and Opportunities
  8. 2024The Visualization JUDGE : Can Multimodal Foundation Models Guide Visualization Design Through Visual Perception?