mlsanityData to 14 Oct 2026

Sensorium Arc: AI Agent System for Oceanic Data Exploration and Interactive Eco-Art

arXiv 2511.15997 ↗First posted 20 Nov 2025cs.AI cs.MMcited by 0

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

Abstract (arXiv)

Sensorium Arc (AI reflects on climate) is a real-time multimodal interactive AI agent system that personifies the ocean as a poetic speaker and guides users through immersive explorations of complex marine data. Built on a modular multi-agent system and retrieval-augmented large language model (LLM) framework, Sensorium enables natural spoken conversations with AI agents that embodies the ocean's perspective, generating responses that blend scientific insight with ecological poetics. Through keyword detection and semantic parsing, the system dynamically triggers data visualizations and audiovisual playback based on time, location, and thematic cues drawn from the dialogue. Developed in collaboration with the Center for the Study of the Force Majeure and inspired by the eco-aesthetic philosophy of Newton Harrison, Sensorium Arc reimagines ocean data not as an abstract dataset but as a living narrative. The project demonstrates the potential of conversational AI agents to mediate affective, intuitive access to high-dimensional environmental data and proposes a new paradigm for human-machine-ecosystem.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 12 of its 31 references that are in the map. First posted on arXiv 20 Nov 2025.

Builds on

12 of 31 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024An LLM Agent for Automatic Geospatial Data Analysis24 Oct

Other references · 11

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2025Why Do Multi-Agent LLM Systems Fail?cited by 604
  3. 2023Query Rewriting for Retrieval-Augmented Large Language Modelscited by 213
  4. 2024Small LLMs Are Weak Tool Learners: A Multi-LLM Agentcited by 93
  5. 2024CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answeringcited by 72
  6. 2024ClimaQA: An Automated Evaluation Framework for Climate Question Answering Modelscited by 21
  7. 2024ChatCam: Empowering Camera Control through Conversational AIcited by 15
  8. 2025Reasoning LLMs for User-Aware Multimodal Conversational Agentscited by 4
  9. 2020Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interactioncited by 2
  10. 2025Improving RAG Retrieval via Propositional Content Extraction: a Speech Act Theory Approachcited by 2
  11. 2025Read the Docs Before Rewriting: Equip Rewriter with Domain Knowledge via Continual Pre-trainingcited by 1

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Close in wording, no citation either way

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