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Found 11 papers, 3 papers with code
The DeepMind Chinese–English Document Translation System at WMT2020
This paper describes the DeepMind submission to the Chinese\rightarrowEnglish constrained data track of the WMT2020 Shared Task on News Translation.
A Natural Bias for Language Generation Models
After just a few hundred training updates, a standard probabilistic model for language generation has likely not yet learnt many semantic or syntactic rules of natural language, making it difficult to estimate the probability distribution over next tokens.
Internet-augmented language models through few-shot prompting for open-domain question answering
In this work, we aim to capitalize on the unique few-shot capabilities of large-scale language models (LSLMs) to overcome some of their challenges with respect to grounding to factual and up-to-date information.
Enabling arbitrary translation objectives with Adaptive Tree Search
When applied to autoregressive models, our algorithm has different biases than beam search has, which enables a new analysis of the role of decoding bias in autoregressive models.
Better Document-Level Machine Translation with Bayes' Rule
We show that Bayes' rule provides an effective mechanism for creating document translation models that can be learned from only parallel sentences and monolingual documents---a compelling benefit as parallel documents are not always available.
Putting Machine Translation in Context with the Noisy Channel Model
We show that Bayes' rule provides a compelling mechanism for controlling unconditional document language models, using the long-standing challenge of effectively leveraging document context in machine translation.
Adversarial Autoencoders for Compact Representations of 3D Point Clouds
Deep generative architectures provide a way to model not only images but also complex, 3-dimensional objects, such as point clouds.
Fashion-Gen: The Generative Fashion Dataset and Challenge
We introduce a new dataset of 293, 008 high definition (1360 x 1360 pixels) fashion images paired with item descriptions provided by professional stylists.
Speaker Diarization using Deep Recurrent Convolutional Neural Networks for Speaker Embeddings
In this paper we propose a new method of speaker diarization that employs a deep learning architecture to learn speaker embeddings.
What Looks Good with my Sofa: Multimodal Search Engine for Interior Design
In this paper, we propose a multi-modal search engine for interior design that combines visual and textual queries.
LanguageCrawl: A Generic Tool for Building Language Models Upon Common-Crawl
The web data contains immense amount of data, hundreds of billion words are waiting to be extracted and used for language research.
