Sentence Embedding Edit Task
Methodology • Sentence Embeddings
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ColBERT: Using BERT Sentence Embedding for Humor Detection
In this paper, we propose a novel approach for detecting humor in short texts based on the general linguistic structure of humor.
A Structured Self-attentive Sentence Embedding
This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention.
NATURAL LANGUAGE INFERENCE SENTENCE EMBEDDING SENTIMENT ANALYSIS
Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation
EMNLP 2020
• UKPLab/sentence-transformers
• 
The training is based on the idea that a translated sentence should be mapped to the same location in the vector space as the original sentence.
Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks
• facebookresearch/InferSent
•
The analysis sheds light on the relative strengths of different sentence embedding methods with respect to these low level prediction tasks, and on the effect of the encoded vector's dimensionality on the resulting representations.
Evaluation of sentence embeddings in downstream and linguistic probing tasks
• allenai/bilm-tf
• 
Despite the fast developmental pace of new sentence embedding methods, it is still challenging to find comprehensive evaluations of these different techniques.
On the Sentence Embeddings from Pre-trained Language Models
EMNLP 2020
• InsaneLife/dssm
•
Pre-trained contextual representations like BERT have achieved great success in natural language processing.
LANGUAGE MODELLING SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY SENTENCE EMBEDDING
Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books
Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and how these states evolve through a story.
DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding
• taoshen58/DiSAN
•
Recurrent neural nets (RNN) and convolutional neural nets (CNN) are widely used on NLP tasks to capture the long-term and local dependencies, respectively.
Ranked #35 on
Natural Language Inference
on SNLI
Concatenated Power Mean Word Embeddings as Universal Cross-Lingual Sentence Representations
• UKPLab/arxiv2018-xling-sentence-embeddings
•
Here, we generalize the concept of average word embeddings to power mean word embeddings.
Hierarchical Attention: What Really Counts in Various NLP Tasks
Ham achieves a state-of-the-art BLEU score of 0. 26 on Chinese poem generation task and a nearly 6. 5% averaged improvement compared with the existing machine reading comprehension models such as BIDAF and Match-LSTM.
MACHINE READING COMPREHENSION MACHINE TRANSLATION SENTENCE EMBEDDING TEXT GENERATION