310 citations
- École Polytechnique Fédérale de LausanneCH87 papers
- Institut Denis PoissonFR42 papers
- Université de ToursFR37 papers
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- Centre National de la Recherche ScientifiqueFR10 papers
- Brno University of TechnologyCZ7 papers
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- University of ManchesterGB7 papers
- Italian Institute of TechnologyIT6 papers
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- Institute for Scientific and Technological ResearchMX5 papers
7 papers · 2 filters
Bag-of-Vectors Autoencoders for Unsupervised Conditional Text Generation
Florian Mai, James Henderson
Text autoencoders are often used for unsupervised conditional text generation by applying mappings in the latent space to change attributes to the desired values. Recently, Mai et…
Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning
Christos Theodoropoulos, James Henderson, Andrei C. Coman +1
Though language model text embeddings have revolutionized NLP research, their ability to capture high-level semantic information, such as relations between entities in text, is lim…
Improving callsign recognition with air-surveillance data in air-traffic communication
Iuliia Nigmatulina, Rudolf Braun, Juan Zuluaga-Gomez +1
Automatic Speech Recognition (ASR) can be used as the assistance of speech communication between pilots and air-traffic controllers. Its application can significantly reduce the co…
A Comparison of Methods for OOV-word Recognition on a New Public Dataset
Rudolf A. Braun, Srikanth Madikeri, Petr Motlicek
A common problem for automatic speech recognition systems is how to recognize words that they did not see during training. Currently there is no established method of evaluating di…
Variational Information Bottleneck for Effective Low-Resource Fine-Tuning
Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson
While large-scale pretrained language models have obtained impressive results when fine-tuned on a wide variety of tasks, they still often suffer from overfitting in low-resource s…
Compacter: Efficient Low-Rank Hypercomplex Adapter Layers
Rabeeh Karimi Mahabadi, James Henderson, Sebastian Ruder
Adapting large-scale pretrained language models to downstream tasks via fine-tuning is the standard method for achieving state-of-the-art performance on NLP benchmarks. However, fi…