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Greatest papers with code

Towards Incremental Learning of Word Embeddings Using Context Informativeness

ACL 2019 minimalparts/nonce2vec

In this paper, we investigate the task of learning word embeddings from very sparse data in an incremental, cognitively-plausible way.

INCREMENTAL LEARNING LEARNING WORD EMBEDDINGS

WordRank: Learning Word Embeddings via Robust Ranking

EMNLP 2016 shihaoji/wordrank

Then, based on this insight, we propose a novel framework WordRank that efficiently estimates word representations via robust ranking, in which the attention mechanism and robustness to noise are readily achieved via the DCG-like ranking losses.

LEARNING WORD EMBEDDINGS

Few-Shot Representation Learning for Out-Of-Vocabulary Words

ACL 2019 acbull/HiCE

Existing approaches for learning word embeddings often assume there are sufficient occurrences for each word in the corpus, such that the representation of words can be accurately estimated from their contexts.

FEW-SHOT REGRESSION LEARNING WORD EMBEDDINGS

Neural Graph Embedding Methods for Natural Language Processing

8 Nov 2019malllabiisc/ConfGCN

Knowledge graphs are structured representations of facts in a graph, where nodes represent entities and edges represent relationships between them.

GRAPH EMBEDDING KNOWLEDGE GRAPHS LEARNING WORD EMBEDDINGS LINK PREDICTION RELATION EXTRACTION

Skip-gram word embeddings in hyperbolic space

30 Aug 2018lateral/minkowski

Recent work has demonstrated that embeddings of tree-like graphs in hyperbolic space surpass their Euclidean counterparts in performance by a large margin.

LEARNING WORD EMBEDDINGS