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Author

Miriam Anschütz

Observed names: Anschütz, Miriam, Miriam Anschutz
Observed institution: Technical University of Munich
OpenAlex ID: A5041007080
This is not correct! Negation-aware Evaluation of Language Generation Systems
2023 · Miriam Anschütz, Diego Miguel Lozano, et al. · International Conference on Natural Language Generation · 13
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An Analysis of Programming Course Evaluations Before and After the Introduction of an Autograder
2021 · Gerhard Hagerer, Laura Lahesoo, et al. · International Conference on Information Technology Based Higher Education and Training (ITHET) · 11
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Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training
2023 · Miriam Anschütz, Joshua Oehms, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · 8
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Retrieving Users’ Opinions on Social Media with Multimodal Aspect-Based Sentiment Analysis
2023 · Miriam Anschütz, Tobias Eder, et al. · IEEE International Conference on Semantic Computing (ICSC) · 4
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Images Speak Volumes: User-Centric Assessment of Image Generation for Accessible Communication
2024 · Miriam Anschütz, Tringa Sylaj, et al. · Workshop on Text Simplification, Accessibility and Readability (TSAR) · 1
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Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering
2026 · Lukas Ellinger, Alexander M. Fichtl, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP)
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MTDiag: A Multi-Turn Diagnostic Dataset Towards Clinically Meaningful LLM Evaluation
2026 · Pia Chouayfati, Alexander M. Fichtl, et al. · Annual Meeting of the Special Interest Group on Discourse and Dialogue
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Diamonds in the rough: Transforming SPARCs of imagination into a game concept by leveraging medium sized LLMs
2025 · Geheeb, Julian, Ivan, Farhan Abid, et al. · arXiv (Cornell University)
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TUM-MiKaNi at SemEval-2025 Task 3: Towards Multilingual and Knowledge-Aware Non-factual Hallucination Identification
2025 · Anschütz, Miriam, Gikalo, Ekaterina, et al. · arXiv (Cornell University)
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Künstliche Intelligenz: Wie funktioniert KI für Einfache Sprache?
2025 · Miriam Anschütz, Silvana Deilen, et al. · Springer eBooks
Simplifications are Absolutists: How Simplified Language ReducesWord Sense Awareness in LLM-Generated Definitions
2025 · Lukas Ellinger, Miriam Anschütz, et al. · International conference Recent advances in natural language processing
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Accessible Communication and Large Language Models: Perspectives on their Mutual Impact and Approaches for German Simplification
2025 · Anschütz, Miriam, Groh, Georg 1970-, et al.
Simpler Becomes Harder: Do LLMs Exhibit a Coherent Behavior on Simplified Corpora?
2024 · Miriam Anschütz, Edoardo Mosca, et al. · Language Resources and Evaluation Conference (LREC)
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Works count: 19
Citation count: 37
H-index: 4
I10-index: 2
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