activity
20212026
most citedLeveraging Large Language Models for Semantic Query Processing in a Scholarly Knowledge Graph

2 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

cs.MA2026

Muscle Memory for Agents: Compile not Merely Retrieve

Pouya Ghiasnezhad Omran, Soujanya Lanka, Qin Zhang +1

Memory for LLM agents has converged on a single architectural pattern: store experience as text, embeddings, reflections, or rules; retrieve at inference time; let a general-purpos…

cs.AI2026

Agent Gym: A Framework for Continuous Evaluation and Evolution of LLM Agents Through Human-in-the-Loop Feedback

Pouya Ghiasnezhad Omran, Michael Zimmermann, Duncan Cambridge +2

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 ed…

cs.IR2026

Reading Between the Citations: A Typed Claim Network for Scientific Literature

Ning Ding, Sergio J. Rodríguez Méndez, Pouya G. Omran

Knowledge graphs over corpora of inter-referencing documents - scholarly papers, legal opinions, policy briefs - encode the topology of reference but not its stance. The standard r…

cs.IR2026

A Systematic Comparison and Evaluation of Building Ontologies for Deploying Data-Driven Analytics in Smart Buildings

Zhangcheng Qiang, Stuart Hands, Kerry Taylor +5

Ontologies play a critical role in data exchange, information integration, and knowledge sharing across diverse smart building applications. Yet, semantic differences between the p…

cs.LG2024

Anomaly Detection and Classification in Knowledge Graphs

Asara Senaratne, Peter Christen, Pouya Omran +1

Anomalies such as redundant, inconsistent, contradictory, and deficient values in a Knowledge Graph (KG) are unavoidable, as these graphs are often curated manually, or extracted u…

cs.IR2024★ 2 cited

Leveraging Large Language Models for Semantic Query Processing in a Scholarly Knowledge Graph

Runsong Jia, Bowen Zhang, Sergio J. Rodríguez Méndez +1

The proposed research aims to develop an innovative semantic query processing system that enables users to obtain comprehensive information about research works produced by Compute…