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Evidence record 6465 · automatically gathered

Exploring Robust Multi-Agent Workflows for Environmental Data Management

Embedding LLM-driven agents into environmental FAIR data management is compelling - they can externalize operational knowledge and scale curation across heterogeneous data and evolving conventions. However, replacing deterministic components with probabilistic workflows changes the failure mode: LLM pipelines may generate plausible but incorrect outputs that pass superficial checks and propagate into irreversible actions such as DOI minting and public release. We introduce EnviSmart, a productio

Record details

Published: 2 April 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy · Environment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Agents & autonomy · Shared topic: Environment

Audio Spatially-Guided Fusion for Audio-Visual Navigation

arXiv · 2 April 2026

Shared topic: Agents & autonomy · Shared topic: Environment

Safety, Security, and Cognitive Risks in World Models

arXiv · 1 April 2026

Shared topic: Agents & autonomy · Shared topic: Environment

Adaptive Memory Crystallization for Autonomous AI Agent Learning in Dynamic Environments

arXiv · 2 April 2026

Shared topic: Agents & autonomy · Shared topic: Environment

Aligning Progress and Feasibility: A Neuro-Symbolic Dual Memory Framework for Long-Horizon LLM Agents

arXiv · 3 April 2026

Shared topic: Agents & autonomy · Shared topic: Environment

AgentHazard: A Benchmark for Evaluating Harmful Behavior in Computer-Use Agents

arXiv · 3 April 2026

Shared topic: Agents & autonomy · Shared topic: Environment

Train the Trainers -- An Agentic AI Framework for Peer-Based Mental Health Support in Battlefield Environments

arXiv · 31 March 2026

How to cite this record

ethics.ai (2 April 2026), “Exploring Robust Multi-Agent Workflows for Environmental Data Management,” evidence record 6465, https://ethics.ai/record/6465 (originally published by arXiv).

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