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Nils Constantin Hellwig

Nils Constantin Hellwig has 2 papers in our library, in 2025–2026, most of them on Sentiment & emotion, Low-resource languages; often with Udo Kruschwitz.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 3 · 27 works · 78 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 4 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #10737

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of RegensburgRegensburg · Germany2024–2026 · 17 papersEmployment since 2024 · PhD Studentcurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Sentiment & emotion · 1 workLow-resource languages · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. German Aspect-based Sentiment Analysis in the Wild: B2B Dataset Creation and Cross-Domain Evaluation (2025 · 3 citations)
    The paper tackles aspect-based sentiment analysis (ABSA) for German in a setting that research rarely covers: Business-to-Business (B2B) software feedback.
  2. schmerle at SemEval-2026 Task 4: Exploring Large Language Model Prompting Strategies for Low-Resource Narrative Similarity Detection (2026 · 1 citation)
    The paper addresses SemEval-2026 Task 4, Track A. Each item is a triple: an anchor story and two candidates. The system must decide which candidate is narratively closer to the anchor, judged by abstract theme, course of action and outcome. The authors use no fine-tuning and no extra annotation. They only prompt…

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. German Aspect-based Sentiment Analysis in the Wild: B2B Dataset Creation and Cross-Domain EvaluationConference on Natural Language ProcessingJakob Fehle, Niklas Donhauser, Udo Kruschwitz, et al.2025 · 3 citations
  2. schmerle at SemEval-2026 Task 4: Exploring Large Language Model Prompting Strategies for Low-Resource Narrative Similarity DetectionInternational Workshop on Semantic Evaluation (SemEval)Maximilian Schmerle, Nils Constantin Hellwig2026 · 1 citation
  3. Annotation Quality in Aspect-Based Sentiment Analysis: A Case Study Comparing Experts, Students, Crowdworkers, and Large Language Models ↗Proceedings of the Fourth Workshop on the Role of Resources in the Age of Large Language Models (RESOURCEFUL 2026) · no summary yetNiklas Donhauser et al.2026
  4. Annotation Quality in Aspect-Based Sentiment Analysis: A Case Study Comparing Experts, Students, Crowdworkers, and Large Language Model ↗arXiv:2605.03624 · no summary yetNiklas Donhauser et al.2026

 Co-authors here

1 co-author with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 4 times (of the 149,439 papers whose bibliographies we read).

Updated

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