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Found 10 papers, 3 papers with code
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.
Comparing Top-Down and Bottom-Up Neural Generative Dependency Models
Recurrent neural network grammars generate sentences using phrase-structure syntax and perform very well on both parsing and language modeling.
The ARIEL-CMU Systems for LoReHLT18
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).
Using Morphological Knowledge in Open-Vocabulary Neural Language Models
Languages with productive morphology pose problems for language models that generate words from a fixed vocabulary.
XNMT: The eXtensible Neural Machine Translation Toolkit
In this paper we describe the design of XNMT and its experiment configuration system, and demonstrate its utility on the tasks of machine translation, speech recognition, and multi-tasked machine translation/parsing.
DyNet: The Dynamic Neural Network Toolkit
In the static declaration strategy that is used in toolkits like Theano, CNTK, and TensorFlow, the user first defines a computation graph (a symbolic representation of the computation), and then examples are fed into an engine that executes this computation and computes its derivatives.
Transition-Based Dependency Parsing with Stack Long Short-Term Memory
We propose a technique for learning representations of parser states in transition-based dependency parsers.
