The Flow has not summarised this story yet — read it at Hugging Face Trending Papers.
The paper introduces LM-DSB, a lightweight multi‑agent system that automates the creation of daily safety bulletins (DSBs) for construction sites using a retrieval‑augmented generation approach with a locally deployable large language model. The system employs specialized planner, researcher, and writer agents coordinated in a hierarchical architecture, fine‑tuned on construction safety documents and grounded in 37 HSE documents. Validation in two phases showed that the multi‑agent RAG system outperformed alternatives in lexical alignment, coherence, and document completeness, and expert reviewers rated it highly for regulatory compliance and factual accuracy.
arXiv:2606. 08531v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evolving from simple text-based interaction systems into LLM agents that can maintain memory, use tools, access external environments, and execute tasks.
arXiv:2606. 29116v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combine natural language understanding with external services and APIs.
PermitGPT is a generative‑AI framework that transforms unstructured construction permit descriptions into structured outputs for safety hazard identification, permit requirement specification, and community impact assessment. It aligns data from the NYC Department of Buildings, OSHA, and NYC 311 to create 90,000 prompt‑response pairs, fine‑tunes three open‑weight language models, and evaluates them on 2,833 test cases, reporting complementary performance across inference speed, lexical overlap, and semantic alignment. The study presents an initial AI‑assisted approach to construction governance and outlines future evaluation and validation directions.
arXiv:2608. 14590v1 Announce Type: new Abstract: LLM agents increasingly perform irreversible real-world actions, including database updates, API calls, file operations, and autonomous use of tools.
arXiv:2608. 15591v1 Announce Type: new Abstract: Large Language Model (LLM) agents deployed in production environments face a fundamental tension: the agent's behavior is frozen at deployment time, while the business rules and edge cases it must handle continue to evolve.