collaborators

6 papers

cs.IR2026

A Triple-Robustness Analysis of Retrieval-Augmented Generation for Multi-Hop Requirements Traceability

Meftun Akarsu, Burak Özdemir, Doğancan Büyükçolak +1

Reported verdicts on GraphRAG versus vector RAG disagree, and the evidence is typically tied to a single corpus, embedder, and judge -- and, we show, to where citation quality is m…

cs.CL2026

Universal Pathologies, Conditional Consequences: A Triple-Robustness Analysis of RAG for Multi-Hop Traceability

Meftun Akarsu, Burak Ozdemir

GraphRAG underperforms vector RAG on citation precision in many reports, but where and why have remained corpus-bound. We present a triple-robustness analysis that holds the retrie…

cs.IR2026

From BM25 to Corrective RAG: Benchmarking Retrieval Strategies for Text-and-Table Documents

Meftun Akarsu, Recep Kaan Karaman, Christopher Mierbach

Retrieval-Augmented Generation (RAG) systems critically depend on retrieval quality, yet no systematic comparison of modern retrieval methods exists for heterogeneous documents con…

cs.SE2025

Code2Doc: A Quality-First Curated Dataset for Code Documentation

Recep Kaan Karaman, Meftun Akarsu

The performance of automatic code documentation generation models depends critically on the quality of the training data used for supervision. However, most existing code documenta…

cs.DB2025

RAG-Driven Data Quality Governance for Enterprise ERP Systems

Sedat Bin Vedat, Enes Kutay Yarkan, Meftun Akarsu +4

Enterprise ERP systems managing hundreds of thousands of employee records face critical data quality challenges when human resources departments perform decentralized manual entry…

cs.CV2025

Fine-Tuning Open Video Generators for Cinematic Scene Synthesis: A Small-Data Pipeline with LoRA and Wan2.1 I2V

Meftun Akarsu, Kerem Catay, Sedat Bin Vedat +4

We present a practical pipeline for fine-tuning open-source video diffusion transformers to synthesize cinematic scenes for television and film production from small datasets. The…