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New frameworks enable asynchronous human-AI collaboration in complex scientific workflows

Researchers have developed HepScript, a Domain-Specific Language (DSL) designed to facilitate human-AI collaboration in high-energy physics data analysis. This DSL abstracts complex analysis logic into a formal syntax that both human experts and AI agents can understand, significantly reducing the amount of human-written code required. In case studies, HepScript enabled AI agents to generate executable analysis specifications from literature with a high success rate, demonstrating a scalable pathway for integrating AI into scientific workflows. AI

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IMPACT New frameworks for human-AI collaboration could streamline complex scientific research and HPC workflows, potentially accelerating discovery and deployment.

RANK_REASON The cluster contains two arXiv papers detailing new frameworks and languages for human-AI collaboration in scientific and HPC environments.

Read on arXiv cs.AI →

COVERAGE [3]

  1. arXiv cs.AI TIER_1 · Sergio Mendoza, Cedric Bhihe, Natalia Zamora, David Modesto, Jose Martin Bugallo Batalla, Jesus Gomez Canovas, Rafel Palomo Avellaneda, Miguel Perez Espinosa ·

    A Workflow-Oriented Framework for Asynchronous Human-AI Collaboration in Hybrid and Compute-Intensive HPC Environments

    arXiv:2605.03743v1 Announce Type: cross Abstract: Human involvement is critical in training and deploying AI systems in high-stakes defence and security contexts. However, real-time interaction is impractical in HPC environments due to compute intensity and resource constraints. …

  2. arXiv cs.AI TIER_1 · Junkun Jiao, Tong Liu, Ke Li, Weimin Song, Yipu Liao, Bolun Zhang, Beijiang Liu, Chang-Zheng Yuan, Yue Sun ·

    HepScript: A Dual-Use DSL for Human-AI Collaborative Data Analysis Workflows in High-Energy Physics

    arXiv:2605.01423v1 Announce Type: cross Abstract: The escalating data scale in High-Energy Physics (HEP) fuels a growing aspiration for higher analytical efficiency. While Large Language Models (LLMs) offer a path toward automation via agentic AI, they struggle with complex scien…

  3. arXiv cs.AI TIER_1 · Miguel Perez Espinosa ·

    A Workflow-Oriented Framework for Asynchronous Human-AI Collaboration in Hybrid and Compute-Intensive HPC Environments

    Human involvement is critical in training and deploying AI systems in high-stakes defence and security contexts. However, real-time interaction is impractical in HPC environments due to compute intensity and resource constraints. We present a workflow framework that enables async…