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Found 40 papers, 9 papers with code
Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields
We apply stochastic average gradient (SAG) algorithms for training conditional random fields (CRFs).
Lexicalized Reordering for Left-to-Right Hierarchical Phrase-based Translation
Phrase-based and hierarchical phrase-based (Hiero) translation models differ radically in the way reordering is modeled.
Prefix Lexicalization of Synchronous CFGs using Synchronous TAG
We show that an epsilon-free, chain-free synchronous context-free grammar (SCFG) can be converted into a weakly equivalent synchronous tree-adjoining grammar (STAG) which is prefix lexicalized.
Top-down Tree Structured Decoding with Syntactic Connections for Neural Machine Translation and Parsing
The addition of syntax-aware decoding in Neural Machine Translation (NMT) systems requires an effective tree-structured neural network, a syntax-aware attention model and a language generation model that is sensitive to sentence structure.
In-domain Context-aware Token Embeddings Improve Biomedical Named Entity Recognition
Here we report on a pipeline built on Embeddings from Language Models (ELMo) and a deep learning package for natural language processing (AllenNLP).
Decipherment for Adversarial Offensive Language Detection
Automated filters are commonly used by online services to stop users from sending age-inappropriate, bullying messages, or asking others to expose personal information.
Prediction Improves Simultaneous Neural Machine Translation
Simultaneous speech translation aims to maintain translation quality while minimizing the delay between reading input and incrementally producing the output.
Sign Clustering and Topic Extraction in Proto-Elamite
We describe a first attempt at using techniques from computational linguistics to analyze the undeciphered proto-Elamite script.
Pointer-based Fusion of Bilingual Lexicons into Neural Machine Translation
Neural machine translation (NMT) systems require large amounts of high quality in-domain parallel corpora for training.
Interrogating the Explanatory Power of Attention in Neural Machine Translation
Attention models have become a crucial component in neural machine translation (NMT).
Deconstructing Supertagging into Multi-Task Sequence Prediction
Supertagging is a sequence prediction task where each word is assigned a piece of complex syntactic structure called a supertag.
Training with Adversaries to Improve Faithfulness of Attention in Neural Machine Translation
Can we trust that the attention heatmaps produced by a neural machine translation (NMT) model reflect its true internal reasoning?
Measuring and Improving Faithfulness of Attention in Neural Machine Translation
While the attention heatmaps produced by neural machine translation (NMT) models seem insightful, there is little evidence that they reflect a model{'}s true internal reasoning.
Better Neural Machine Translation by Extracting Linguistic Information from BERT
Adding linguistic information (syntax or semantics) to neural machine translation (NMT) has mostly focused on using point estimates from pre-trained models.
CipherDAug: Ciphertext based Data Augmentation for Neural Machine Translation
We propose a novel data-augmentation technique for neural machine translation based on ROT-$k$ ciphertexts.
Ranked #9 on
Machine Translation
on IWSLT2014 German-English
SpEL: Structured Prediction for Entity Linking
Entity linking is a prominent thread of research focused on structured data creation by linking spans of text to an ontology or knowledge source.
Ranked #1 on
Entity Linking
on AIDA/testc
(using extra training data)
Effectively pretraining a speech translation decoder with Machine Translation data
Directly translating from speech to text using an end-to-end approach is still challenging for many language pairs due to insufficient data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Auxiliary Subword Segmentations as Related Languages for Low Resource Multilingual Translation
We propose a novel technique that combines alternative subword tokenizations of a single source-target language pair that allows us to leverage multilingual neural translation training methods.
Translation-based Supervision for Policy Generation in Simultaneous Neural Machine Translation
In simultaneous machine translation, finding an agent with the optimal action sequence of reads and writes that maintain a high level of translation quality while minimizing the average lag in producing target tokens remains an extremely challenging problem.
