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Fatemeh H. Fard
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Fatemeh H. Fard11 visible / 11 total nodes / 33 links

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Related contextRelated contextRelated contextCo-authorshipCo-authorshipCo-authorshipWorks onWorks onWorks onWorks onAuthorshipWorks onWorks onWorks onWorks onWorks onAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalTopic signalAuthorshipFatemeh H. FardAFatemeh H. FardResearcherMohamad KhajezadeAMohamad KhajezadeResearcherMohamed Sami ShehataAMohamed Sami ShehataResearcherArtificial IntelligenceTArtificial Intelligence22915 worksMachine LearningTMachine Learning49008 worksSoftware EngineeringTSoftware Engineering3620 worksStanding on the Shoulders of Giants: Stabilized Knowledge Distillation for Cross--Language Code Clone DetectionWStanding on the Shoulde...preprint / 2026Pre-Trained Neural Language Models for Automatic Mobile App User Feedback Answer GenerationWPre-Trained Neural Lang...preprint / 2022Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-ReviewsWEvaluating Pre-Trained ...preprint / 2022On The Cross-Modal Transfer from Natural Language to Code through Adapter ModulesWOn The Cross-Modal Tran...preprint / 2022On the Effectiveness of Pretrained Models for API LearningWOn the Effectiveness of...preprint / 2022
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Fatemeh H. Fard

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PersonMohamad KhajezadeCo-authorship / ResearcherPersonMohamed Sami ShehataCo-authorship / ResearcherTopicArtificial IntelligenceWorks on / 22915 worksTopicMachine LearningWorks on / 49008 worksTopicSoftware EngineeringWorks on / 3620 worksPaperStanding on the Shoulders of Giants: Stabilized Knowledge Distillation for Cross--Language Code Clone DetectionAuthorship / preprint / 2026PaperPre-Trained Neural Language Models for Automatic Mobile App User Feedback Answer GenerationAuthorship / preprint / 2022PaperEvaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-ReviewsAuthorship / preprint / 2022

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