What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Programming language
- Machine learning
Her main research concerns Artificial intelligence, Natural language processing, Machine learning, Parsing and Domain.
Her Artificial intelligence research integrates issues from Agreement and Reliability.
Barbara Plank interconnects Syntax and Word in the investigation of issues within Natural language processing.
Her Word course of study focuses on Character and Speech recognition and Part-of-speech tagging.
Her Machine learning research is multidisciplinary, incorporating elements of Space and Data mining.
Her studies deal with areas such as Sentiment analysis and Similarity as well as Domain.
Her most cited work include:
- Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss (320 citations)
- Automatic description generation from images: a survey of models, datasets, and evaluation measures (184 citations)
- When is multitask learning effective? Semantic sequence prediction under varying data conditions (114 citations)
What are the main themes of her work throughout her whole career to date?
Artificial intelligence, Natural language processing, Parsing, Domain and Machine learning are her primary areas of study.
Barbara Plank conducts interdisciplinary study in the fields of Artificial intelligence and Generalization through her research.
Her biological study focuses on Dependency grammar.
Her Domain research incorporates elements of Software portability and Baseline.
Her Machine learning research is multidisciplinary, incorporating perspectives in Multi-task learning, Sequence labeling and Benchmark.
Her research in Syntax intersects with topics in Treebank and Universal dependencies.
She most often published in these fields:
- Artificial intelligence (79.84%)
- Natural language processing (68.22%)
- Parsing (18.60%)
What were the highlights of her more recent work (between 2018-2021)?
- Artificial intelligence (79.84%)
- Natural language processing (68.22%)
- Syntax (13.95%)
In recent papers she was focusing on the following fields of study:
Barbara Plank spends much of her time researching Artificial intelligence, Natural language processing, Syntax, Danish and Treebank.
The study incorporates disciplines such as Lexical knowledge and Machine learning in addition to Artificial intelligence.
Her Machine learning study integrates concerns from other disciplines, such as Information extraction and Probabilistic logic.
Language model is the focus of her Natural language processing research.
Her work in Danish tackles topics such as Named-entity recognition which are related to areas like Cross lingual, Training set, Normalization and German.
Her Range study incorporates themes from Word, Semantics, Unsupervised learning and Set.
Between 2018 and 2021, her most popular works were:
- Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat (27 citations)
- The Lacunae of Danish Natural Language Processing (12 citations)
- Psycholinguistics Meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering (9 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Machine learning
Barbara Plank focuses on Artificial intelligence, Natural language processing, Universal dependencies, Dependency and Treebank.
Barbara Plank undertakes interdisciplinary study in the fields of Artificial intelligence and Coronavirus disease 2019 through her research.
Barbara Plank conducted interdisciplinary study in her works that combined Natural language processing and Political science.
Her Universal dependencies study frequently intersects with other fields, such as Syntax.
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