Sudachi: a Japanese Tokenizer for Business

WorksApplications/Sudachi • LREC 2018

Contextual String Embeddings for Sequence Labeling

zalandoresearch/flair • • COLING 2018

Recent advances in language modeling using recurrent neural networks have made it viable to model language as distributions over characters.

Sequence Labeling: A Practical Approach

aakhundov/sequence-labeling • • 12 Aug 2018

We take a practical approach to solving sequence labeling problem assuming unavailability of domain expertise and scarcity of informational and computational resources.

Large scale visual place recognition with sub-linear storage growth

intellhave/SublinearEncoding • 23 Oct 2018

Robotic and animal mapping systems share many of the same objectives and challenges, but differ in one key aspect: where much of the research in robotic mapping has focused on solving the data association problem, the grid cell neurons underlying maps in the mammalian brain appear to intentionally break data association by encoding many locations with a single grid cell neuron.

FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP

zalandoresearch/flair • • NAACL 2019

We present FLAIR, an NLP framework designed to facilitate training and distribution of state-of-the-art sequence labeling, text classification and language models.

GCDT: A Global Context Enhanced Deep Transition Architecture for Sequence Labeling

Adaxry/GCDT • • ACL 2019

Current state-of-the-art systems for sequence labeling are typically based on the family of Recurrent Neural Networks (RNNs).

Augmenting Neural Networks with First-order Logic

utahnlp/layer_augmentation • • ACL 2019

Today, the dominant paradigm for training neural networks involves minimizing task loss on a large dataset.

Language-Agnostic Syllabification with Neural Sequence Labeling

jacobkrantz/lstm-syllabify • • 29 Sep 2019

The concept of the syllable is cross-linguistic, though formal definitions are rarely agreed upon, even within a language.

Gated Task Interaction Framework for Multi-task Sequence Tagging

kaeflint/GTI • 29 Sep 2019

Others have shown that linguistic features can improve the performance of neural models on tasks such as chunking and named entity recognition (NER).

CmnRec: Sequential Recommendations with Chunk-accelerated Memory Network

SLQu/CmnRec • • 28 Apr 2020

Specifically, our framework divides proximal information units into chunks, and performs memory access at certain time steps, whereby the number of memory operations can be greatly reduced.