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The presentation reports on the on-going work to automatically process heterogeneous historical documents. After a quick overview of the general processing pipeline, a few examples are more comprehensively described. The recent progress in making large col ...
Keyphrase extraction is the task of automatically selecting a small set of phrases that best describe a given free text document. Keyphrases can be used for indexing, searching, aggregating and summarizing text documents, serving many automatic as well as ...
Different senses of source words must often be rendered by different words in the target language when performing machine translation (MT). Selecting the correct translation of polysemous words can be done based on the contexts of use. However, state-of-th ...
We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms. The dataset comprises 199 real, fully annotated, scanned forms. The documents are noisy and vary widely ...
The paper describes the submission of the team "We used bert!" to the shared task Gendered Pronoun Resolution (Pair pronouns to their correct entities). Our final submission model based on the fine-tuned BERT (Bidirectional Encoder Representations from Tra ...
Defining and identifying duplicate records in a dataset is a challenging task which grows more complex when the modeled entities themselves are hard to delineate. In the geospatial domain, it may not be clear where a mountain, stream, or valley ends and be ...
In this thesis, we present a transformers-based multi-lingual embedding model to represent sentences in different languages in a common space. To do so, our system uses the structure of a simplified transformer with a shared byte-pair encoding vocabulary f ...
Linking facts across documents is a challenging task, as the language used to express the same information in a sentence can vary significantly, which complicates the task of multi-document summarization. Consequently, existing approaches heavily rely on h ...
Distributed representations of words which map each word to a continuous vector have proven useful in capturing important linguistic information not only in a single language but also across different languages. Current unsupervised adversarial approaches ...
The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousa ...