Search Results for author:
Found 15 papers, 5 papers with code
A Sentiment-annotated Dataset of English Causal Connectives
This paper investigates the semantic prosody of three causal connectives: due to, owing to and because of in seven varieties of the English language.
Disambiguation of Potentially Idiomatic Expressions with Contextual Embeddings
The unsupervised classification, similarly, yields very impressive results, comparing favorably to the supervised classifier for the majority of the expressions.
Let’s be explicit about that: Distant supervision for implicit discourse relation classification via connective prediction
We sidestep the lack of data through explicitation of implicit relations to reduce the task to two sub-problems: language modeling and explicit discourse relation classification, a much easier problem.
Classification
Implicit Discourse Relation Classification
+4
Evaluation of really good grammatical error correction
We find that GPT-3 in a few-shot setting by far outperforms previous grammatical error correction systems for Swedish, a language comprising only 0. 11% of its training data.
Language Embeddings Sometimes Contain Typological Generalizations
To what extent can neural network models learn generalizations about language structure, and how do we find out what they have learned?
Probing Multilingual Language Models for Discourse
Pre-trained multilingual language models have become an important building block in multilingual natural language processing.
Let's be explicit about that: Distant supervision for implicit discourse relation classification via connective prediction
We sidestep the lack of data through explicitation of implicit relations to reduce the task to two sub-problems: language modeling and explicit discourse relation classification, a much easier problem.
Classification
Implicit Discourse Relation Classification
+4
Zero-shot transfer for implicit discourse relation classification
Automatically classifying the relation between sentences in a discourse is a challenging task, in particular when there is no overt expression of the relation.
What do Language Representations Really Represent?
If the corpus is multilingual, the same model can be used to learn distributed representations of languages, such that similar languages end up with similar representations.
The Helsinki Neural Machine Translation System
We also discuss our submissions for English--Latvian, English--Chinese and Chinese--English.
Neural machine translation for low-resource languages
Neural machine translation (NMT) approaches have improved the state of the art in many machine translation settings over the last couple of years, but they require large amounts of training data to produce sensible output.
SU-RUG at the CoNLL-SIGMORPHON 2017 shared task: Morphological Inflection with Attentional Sequence-to-Sequence Models
This paper describes the Stockholm University/University of Groningen (SU-RUG) system for the SIGMORPHON 2017 shared task on morphological inflection.
Articulation rate in Swedish child-directed speech increases as a function of the age of the child even when surprisal is controlled for
In earlier work, we have shown that articulation rate in Swedish child-directed speech (CDS) increases as a function of the age of the child, even when utterance length and differences in articulation rate between subjects are controlled for.
Continuous multilinguality with language vectors
Most existing models for multilingual natural language processing (NLP) treat language as a discrete category, and make predictions for either one language or the other.
Inferring the location of authors from words in their texts
This paper describes a series of experiments to determine how positionally annotated microblog posts can be used to learn location-indicating words which then can be used to locate blog texts and their authors.
