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Ute Schmid

4 papers hereh-index 270 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • cs.CY1
  • cs.IR1
  • cs.SE1
same name
  • Ute Schmid — 9 papers, h 27
  • Ute Schmid — 8 papers, h 10
  • Ute Schmid — 4 papers, h 1
  • Ute Schmid — 3 papers, h 3
  • Ute Schmid — 2 papers, h 3
  • Ute Schmid — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedKnowledge graph enhanced retrieval-augmented generation for failure mode and effects analysis

54 citations · 54 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CY2025

Why do women pursue a PhD in Computer Science?

Erika Ábrahám, Miguel Goulão, Milena Vujošević Janičić +13

Computer science attracts few women, and their proportion decreases through advancing career stages. Few women progress to PhD studies in CS after completing master's studies. Empo…

cs.SE2025

USeR: A Web-based User Story eReviewer for Assisted Quality Optimizations

Daniel Hallmann, Kerstin Jacob, Gerald Lüttgen +2

User stories are widely applied for conveying requirements within agile software development teams. Multiple user story quality guidelines exist, but authors like Product Owners in…

cs.CV2024

Interactive Explainable Anomaly Detection for Industrial Settings

Daniel Gramelt, Timon Höfer, Ute Schmid

Being able to recognise defects in industrial objects is a key element of quality assurance in production lines. Our research focuses on visual anomaly detection in RGB images. Alt…

cs.IR2024★ 54 cited

Knowledge graph enhanced retrieval-augmented generation for failure mode and effects analysis

Lukas Bahr, Christoph Wehner, Judith Wewerka +3

Failure mode and effects analysis (FMEA) is an essential tool for mitigating potential failures, particularly during the ramp-up phases of new products. However, its effectiveness…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.