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Notes on automation
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From Threat Intelligence to Detection: Knowledge-driven Enrichment and Template-based Rule Grounding for Automated Sigma Rule Generation
The paper presents AUTOSIGMA, a system that automates the transformation of unstructured cyber threat intelligence (CTI) reports into relevant Sigma rules for threat detection. Instead of solely relying on language…
CliniSense AI for automated clinical skills assessment with real-time feedback
Two articles discuss the development of AI systems for clinical skills assessment and a virtual trial framework for generating clinical evidence in orthopedics.
OmniScientist: An Omni-Modal Omni-Discipline AI Scientist
Researchers have developed OmniScientist, an AI system that can conduct multidisciplinary research from raw data across various modalities (text, images, signals, etc.). The system operates in a deterministic pipeline…
Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models
The study introduces a framework to automate the construction of Dynamic Master Logic (DML) models for complex systems using Retrieval-Augmented Generation and Large Language Models. These models, represented as…
GUIDE: Governed Unified Intelligence for Document-to-Artifact Generation in Enterprise Settings
The paper introduces GUIDE, a framework designed to automate the creation of enterprise guideline documents. The system uses six specialized agents to parse, extract, check consistency, evaluate, escalate human…
Tracing the Heart: An Evidence-Linked Pipeline for Heart-Failure Feature Engineering
Researchers developed an automated system called nMAS for heart-failure feature engineering in electronic health records (EHR). The system generates structured and aggregated features that were verified and audited…
The Boundaries of Automation: A Theory of Persistent Human Participation
This research paper questions the assumption that as AI becomes more capable, human participation in tasks will decrease. Instead, it argues that there are three reasons why human participation may persist even with…
Automated Extraction of Techno-Economic Data from 76,000 Energy System Studies
Researchers developed a method to automatically extract quantitative information from 76,000 energy system studies published since 2010. They compiled over 3 million structured data points and 20 million metadata…
Human Grounded Evaluation of Large Language Models for Optical Network Automation
The paper introduces a new evaluation pipeline named HuGLEN for comparing large language models (LLMs) used in network automation. The pipeline uses an LLM to evaluate other LLMs and rates them based on a quality…
Explaining Process Control Optimisation Recommendations via GradientSHAP and Implicit Differentiation
A new approach is presented to explain optimization recommendations in industrial processes using GradientSHAP, Implicit Function Theorem (IFT), and Large Language Models (LLM). The method provides efficient and…
LQCDMaster: Agentic Scientific Computing for Lattice Quantum Chromodynamics Research
The authors present LQCDMaster, a tool that converts natural language Lattice Quantum Chromodynamics (LQCD) research tasks into executable Python scripts for computing workflows. The system reduces implementation time…
LQCDMaster: Agentic Scientific Computing for Lattice Quantum Chromodynamics Research
A group of researchers have developed a tool called LQCDMaster, which is an agent designed to simplify computational tasks in lattice quantum chromodynamics (LQCD) research. The tool can convert natural language…
SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisions
The text is about a new system called SciDiagramEdit that automates the editing of scientific diagrams in research papers based on natural language instructions. The system learns from revisions made to figures in…
GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
The paper introduces a new multi-agent coding harness called Graph-as-Policy (GaP) for improving the reliability of robots in commercial and industrial applications, specifically focusing on variational automation…
Toward Trustworthy Large Language Model Agents in Healthcare
A study presents CareConnect, a safety-first conversational agent for automating healthcare appointment scheduling using large language models (LLMs), retrieval-augmented generation (RAG), and safety guardrails. The…
Rehearsed Multi-Agent Live Product Demonstrations with Real-Time Voice Question Answering
The authors propose Rhetor, a multi-agent system that automates live product demonstrations by merging UI exploration and source-code analysis, producing rehearsed demos with synchronized narration and real-time voice…
Automating Potential-based Reward Shaping with Vision Language Model Guidance
In this research, the authors propose a new method called VLM-PBRS for automating potential-based reward shaping using vision language model (VLM) feedback. The goal is to help reinforcement learning agents learn from…
Automating Potential-based Reward Shaping with Vision Language Model Guidance
Researchers introduce a new method called VLM-PBRS for automating potential-based reward shaping using vision language model (VLM) feedback. The aim is to improve reinforcement learning agents' ability to learn from…
Probabilistic Agents in Deterministic Audits: Evaluating Multi-Agent Systems for Automated Audits Based on the German IT-Grundschutz
This research paper presents a Multi-Agent System (MAS) architecture with Hybrid Retrieval Augmented Generation (HybridRAG) for partially automating IT-Grundschutz certification, a German standard for IT security. The…
MacAgentBench: Benchmarking AI Agents on Real-World macOS Desktop
Researchers have developed a new benchmark for AI agents on macOS desktops called MacAgentBench. The benchmark includes 676 tasks across 25 applications and measures the performance of various models using a…
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