collaborators

7 papers

cs.AI2026

DiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rules

Devin Yasith De Silva, Dhaval Patel, Christodoulos Constantinides +7

Monitoring complex industrial assets relies on engineer-authored symbolic rules that trigger based on sensor conditions and prompt technicians to perform corrective actions. The bo…

cs.AI2026

Transduction is All You Need for Structured Data Workflows

Alfio Gliozzo, Naweed Khan, Christodoulos Constantinides +4

This paper introduces Agentics, a functional agentic AI framework for building LLM-based structured data workflow pipelines. Designed for both research and practical applications,…

cs.CL2025

Fine-Tuned Thoughts: Leveraging Chain-of-Thought Reasoning for Industrial Asset Health Monitoring

Shuxin Lin, Dhaval Patel, Christodoulos Constantinides

Small Language Models (SLMs) are becoming increasingly popular in specialized fields, such as industrial applications, due to their efficiency, lower computational requirements, an…

cs.CL2025

Towards Building General Purpose Embedding Models for Industry 4.0 Agents

Christodoulos Constantinides, Shuxin Lin, Dhaval Patel

In this work we focus on improving language models' understanding for asset maintenance to guide the engineer's decisions and minimize asset downtime. Given a set of tasks expresse…

cs.CL2025

Chat-of-Thought: Collaborative Multi-Agent System for Generating Domain Specific Information

Christodoulos Constantinides, Shuxin Lin, Nianjun Zhou +1

This paper presents a novel multi-agent system called Chat-of-Thought, designed to facilitate the generation of Failure Modes and Effects Analysis (FMEA) documents for industrial a…

cs.CL2025

FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes

Christodoulos Constantinides, Dhaval Patel, Shuxin Lin +3

We introduce FailureSensorIQ, a novel Multi-Choice Question-Answering (MCQA) benchmarking system designed to assess the ability of Large Language Models (LLMs) to reason and unders…