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Michael A. Hedderich
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Michael A. Hedderich12 visible / 12 total nodes / 27 links

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Co-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipWorks onWorks onAuthorshipWorks onAuthorshipWorks onAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalAuthorshipMichael A. HedderichAMichael A. HedderichResearcherCrosslingual On-Policy Self-Distillation for Multilingual ReasoningWCrosslingual On-Policy ...preprint / 2026Yihong LiuAYihong LiuResearcherRaoyuan ZhaoARaoyuan ZhaoResearcherHinrich SchützeAHinrich SchützeResearcherAnalysing the Noise Model Error for Realistic Noisy Label DataWAnalysing the Noise Mod...preprint / 2021Computation and LanguageTComputation and Language14115 worksIs BERT Robust to Label Noise? A Study on Learning with Noisy Labels in Text ClassificationWIs BERT Robust to Label...preprint / 2022Task-Adaptive Pre-Training for Boosting Learning With Noisy Labels: A Study on Text Classification for African LanguagesWTask-Adaptive Pre-Train...preprint / 2022Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and YorùbáWDistant Supervision and...preprint / 2020MCSE: Multimodal Contrastive Learning of Sentence EmbeddingsWMCSE: Multimodal Contra...preprint / 2022Linear Script Representations in Speech Foundation Models Enable Zero-Shot TransliterationWLinear Script Represent...preprint / 2026
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Michael A. Hedderich

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PaperCrosslingual On-Policy Self-Distillation for Multilingual ReasoningAuthorship / preprint / 2026PersonYihong LiuCo-authorship / ResearcherPersonRaoyuan ZhaoCo-authorship / ResearcherPersonHinrich SchützeCo-authorship / ResearcherPaperAnalysing the Noise Model Error for Realistic Noisy Label DataAuthorship / preprint / 2021TopicComputation and LanguageWorks on / 14115 worksPaperIs BERT Robust to Label Noise? A Study on Learning with Noisy Labels in Text ClassificationAuthorship / preprint / 2022PaperTask-Adaptive Pre-Training for Boosting Learning With Noisy Labels: A Study on Text Classification for African LanguagesAuthorship / preprint / 2022

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