most citedDeep Learning for Answer Sentence Selection

354 citations · 538 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI201949 cited

The StreetLearn Environment and Dataset

Piotr Mirowski, Andras Banki-Horvath, Keith Anderson +8

Navigation is a rich and well-grounded problem domain that drives progress in many different areas of research: perception, planning, memory, exploration, and optimisation in parti…

cs.CL2014354 cited

Deep Learning for Answer Sentence Selection

Lei Yu, Karl Moritz Hermann, Phil Blunsom +1

Answer sentence selection is the task of identifying sentences that contain the answer to a given question. This is an important problem in its own right as well as in the larger c…

cs.CL201410 cited

Distributed Representations for Compositional Semantics

Karl Moritz Hermann

The mathematical representation of semantics is a key issue for Natural Language Processing (NLP). A lot of research has been devoted to finding ways of representing the semantics…

cs.CL201442 cited

Learning Bilingual Word Representations by Marginalizing Alignments

Tomáš Kočiský, Karl Moritz Hermann, Phil Blunsom

We present a probabilistic model that simultaneously learns alignments and distributed representations for bilingual data. By marginalizing over word alignments the model captures…

cs.CL201411 cited

A Deep Architecture for Semantic Parsing

Edward Grefenstette, Phil Blunsom, Nando de Freitas +1

Many successful approaches to semantic parsing build on top of the syntactic analysis of text, and make use of distributional representations or statistical models to match parses…

cs.CL201472 cited

Multilingual Models for Compositional Distributed Semantics

Karl Moritz Hermann, Phil Blunsom

We present a novel technique for learning semantic representations, which extends the distributional hypothesis to multilingual data and joint-space embeddings. Our models leverage…