431 citations · 857 across the 69 of their papers we have counts for
9 papers · 2 filters
Jointly Learning to Label Sentences and Tokens
Marek Rei, Anders Søgaard
Learning to construct text representations in end-to-end systems can be difficult, as natural languages are highly compositional and task-specific annotated datasets are often limi…
Why is unsupervised alignment of English embeddings from different algorithms so hard?
Mareike Hartmann, Yova Kementchedjhieva, Anders Søgaard
This paper presents a challenge to the community: Generative adversarial networks (GANs) can perfectly align independent English word embeddings induced using the same algorithm, b…
Nightmare at test time: How punctuation prevents parsers from generalizing
Anders Søgaard, Miryam de Lhoneux, Isabelle Augenstein
Punctuation is a strong indicator of syntactic structure, and parsers trained on text with punctuation often rely heavily on this signal. Punctuation is a diversion, however, since…
A strong baseline for question relevancy ranking
Ana V. González-Garduño, Isabelle Augenstein, Anders Søgaard
The best systems at the SemEval-16 and SemEval-17 community question answering shared tasks -- a task that amounts to question relevancy ranking -- involve complex pipelines and ma…
A Discriminative Latent-Variable Model for Bilingual Lexicon Induction
Sebastian Ruder, Ryan Cotterell, Yova Kementchedjhieva +1
We introduce a novel discriminative latent variable model for bilingual lexicon induction. Our model combines the bipartite matching dictionary prior of Haghighi et al. (2008) with…
Parameter sharing between dependency parsers for related languages
Miryam de Lhoneux, Johannes Bjerva, Isabelle Augenstein +1
Previous work has suggested that parameter sharing between transition-based neural dependency parsers for related languages can lead to better performance, but there is no consensu…