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Thomas Seidl

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2017 · Seidl, Thomas, Kröger, Peer, et al. · Lecture notes in computer science · 3
PRSM: A Measure to Evaluate CLIP’s Robustness Against Paraphrases
2026 · Udo Schlegel, Franziska Weeber, et al. · Lecture notes in computer science · 1
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Vision–Language-Guided Pseudo-Labels for Unsupervised Domain Adaptation in Semantic Segmentation for Waste Sorting
2026 · Udo Schlegel, Shubhangi, et al. · Lecture notes in computer science
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IMFACT: Counterfactual Explanations for Time Series via Intrinsic Mode Function Substitution
2026 · Schlegel, Udo, Rakuschek, Julian, et al. · arXiv (Cornell University)
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Masterarbeit
2026 · Thomas Seidl · OSF Preprints (OSF Preprints)
ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning -- Additional Material
2026 · Matthews, Pernille, Krieger, Lena, et al. · arXiv (Cornell University)
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ForgeVLA: Federated Vision-Language-Action Learning without Language Annotations
2026 · Zhou, Yuhao, Zhu, Yunpeng, et al. · arXiv (Cornell University)
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NICE FACT: Diagnosing and Calibrating VLMs in Quantitative Reasoning for Kinematic Physics
2026 · Lan, Jian, Liu, Zhicheng, et al. · arXiv (Cornell University)
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Wissenschaftliches Projekt
2026 · Thomas Seidl · OSF Preprints (OSF Preprints)
Know Your Streams: On the Conceptualization, Characterization, and Generation of Intentional Event Streams
2026 · Maldonado, Andrea, Imenkamp, Christian, et al. · arXiv (Cornell University)
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What-If Explanations Over Time: Counterfactuals for Time Series Classification
2026 · Schlegel, Udo, Seidl, Thomas · arXiv (Cornell University)
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DCMatchBoosted - improving deep clustering by architecture recommendation
2026 · Mamdouh Aljoud, Gabriel Marques Tavares, et al. · International Journal of Data Science and Analytics
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What's in the Bottle? A Survey and Roadmap of Concept Bottleneck Models
2026 · Knab, Patrick, Steinmann, David, et al. · MPG.PuRe (Max Planck Society)
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Beyond Input Understanding: Diagnosing Multilingual Mathematical Reasoning with Directed Acyclic Trace Graphs
2026 · Jiaqiao Zhang, Zhoujun Li, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP)
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From Black-Box to Collaborative: Position Paper on Human-Guided Trace Clustering
2026 · Schlegel, Udo, Tavares, Gabriel Marques, et al. · Eurographics
MNN-Closure Meets Local Maxima: A Double-Knee Approach to Anomaly Detection
2025 · Walid Durani, Philipp Jahn, et al. · Proceedings
Unveiling the "Fairness Seesaw": Discovering and Mitigating Gender and Race Bias in Vision-Language Models
2025 · Lan, Jian, Schlegel, Udo, et al. · arXiv (Cornell University)
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Works count: 17
Citation count: 4
H-index: 1
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