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Disambiguation of "Dredze, Mark"

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Model Distillation for Faithful Explanations of Medical Code Predictions.

, , and . BioNLP@ACL, page 412-425. Association for Computational Linguistics, (2022)

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Mark Yampolsky

Maßnahmen zur Sicherung von E2E-QoS bei verketteten Diensten. Uni München, (2009)

Mark Schütte

Crf2 - ein neues Antigen von Aspergillus fumigatus. TU Braunschweig, (2009)

Mark Yampolskiy

Maßnahmen zur Sicherung von E2E-QoS bei verketteten Diensten. Uni München, (2009)

Ana Markovi

Experimental and theoretical analysis of the mass transport through porous glass membranes with different pore diameters. Uni Magdeburg, (2009)

Mark Michael

 

Other publications of authors with the same name

Visual Attention Model for Cross-sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning., , , , , and . CoRR, (2018)Learning Fast Classifiers for Image Spam., , and . CEAS, (2007)Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement., , , , and . CoRR, (2020)Approximation-Aware Dependency Parsing by Belief Propagation., , and . Trans. Assoc. Comput. Linguistics, (2015)Twitter as a Source of Global Mobility Patterns for Social Good., , , and . CoRR, (2016)Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions., , , and . CoRR, (2024)Entity Clustering Across Languages., , , , and . HLT-NAACL, page 60-69. The Association for Computational Linguistics, (2012)Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction., , and . HLT-NAACL, page 1374-1379. The Association for Computational Linguistics, (2015)Contextual Information Improves OOV Detection in Speech., , , and . HLT-NAACL, page 216-224. The Association for Computational Linguistics, (2010)Convolutions Are All You Need (For Classifying Character Sequences)., , and . NUT@EMNLP, page 208-213. Association for Computational Linguistics, (2018)