Springer Nature OA
open access
CC BY 4.0
An exploration of safety analytics for proactivity in workplace safety using large language models
Recent technological developments underpinning advanced analytical methods enable safety critical entities to unravel insights from voluminous data accumulated in their repositories. A prominent disruptive technology that is gaining momentum in computational linguistics is large language models (LLM
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Benchmarking Language Models for Clinical Safety: A Primer for Mental Health Professionals#130504
- Benchmarking Language Models for Clinical Safety: A Primer for Mental Health Professionals#68022
- From COBIT to ISO 42001: Evaluating cybersecurity frameworks for opportunities, risks, and regulatory compliance in commercializing large language models#671848
- ForesightSafety-SAGE:A Fully Automated Scenario Generation and Safety Evaluation Framework for LLM Agents#800068
- Safety in Self-Evolving Agents: A Survey#1154716
Record · ID 1092576
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive