A survey on deep learning: Algorithms, techniques, and applications
The field of machine learning is witnessing its golden era as deep learning slowly becomes
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …
A survey of the usages of deep learning for natural language processing
Over the last several years, the field of natural language processing has been propelled
forward by an explosion in the use of deep learning models. This article provides a brief …
forward by an explosion in the use of deep learning models. This article provides a brief …
Atlas: Few-shot learning with retrieval augmented language models
Large language models have shown impressive few-shot results on a wide range of tasks.
However, when knowledge is key for such results, as is the case for tasks such as question …
However, when knowledge is key for such results, as is the case for tasks such as question …
Recommendation as instruction following: A large language model empowered recommendation approach
In the past decades, recommender systems have attracted much attention in both research
and industry communities, and a large number of studies have been devoted to developing …
and industry communities, and a large number of studies have been devoted to developing …
A neural corpus indexer for document retrieval
Current state-of-the-art document retrieval solutions mainly follow an index-retrieve
paradigm, where the index is hard to be directly optimized for the final retrieval target. In this …
paradigm, where the index is hard to be directly optimized for the final retrieval target. In this …
Multimodal intelligence: Representation learning, information fusion, and applications
Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …
natural language processing since 2010. Each of these tasks involves a single modality in …
Convolutional 2d knowledge graph embeddings
T Dettmers, P Minervini, P Stenetorp… - Proceedings of the AAAI …, 2018 - ojs.aaai.org
Link prediction for knowledge graphs is the task of predicting missing relationships between
entities. Previous work on link prediction has focused on shallow, fast models which can …
entities. Previous work on link prediction has focused on shallow, fast models which can …
Distilling knowledge from reader to retriever for question answering
The task of information retrieval is an important component of many natural language
processing systems, such as open domain question answering. While traditional methods …
processing systems, such as open domain question answering. While traditional methods …
A survey on dialogue systems: Recent advances and new frontiers
Dialogue systems have attracted more and more attention. Recent advances on dialogue
systems are overwhelmingly contributed by deep learning techniques, which have been …
systems are overwhelmingly contributed by deep learning techniques, which have been …
The importance of modeling social factors of language: Theory and practice
Natural language processing (NLP) applications are now more powerful and ubiquitous
than ever before. With rapidly developing (neural) models and ever-more available data …
than ever before. With rapidly developing (neural) models and ever-more available data …