Sentence Embedding
132 papers with code • 0 benchmarks • 7 datasets
Benchmarks
These leaderboards are used to track progress in Sentence Embedding
Libraries
Use these libraries to find Sentence Embedding models and implementations
Tatoeba
UR-FUNNY
Video2GIF
Most implemented papers
InfoCSE: Information-aggregated Contrastive Learning of Sentence Embeddings
caskcsg/sentemb
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Contrastive learning has been extensively studied in sentence embedding learning, which assumes that the embeddings of different views of the same sentence are closer.
miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings
This study opens up avenues for efficient self-supervised learning methods that are more robust than current contrastive methods for sentence embedding.
Sentence Embedding Models for Ancient Greek Using Multilingual Knowledge Distillation
In this work, we use a multilingual knowledge distillation approach to train BERT models to produce sentence embeddings for Ancient Greek text.
Simple Techniques for Enhancing Sentence Embeddings in Generative Language Models
Sentence Embedding stands as a fundamental task within the realm of Natural Language Processing, finding extensive application in search engines, expert systems, and question-and-answer platforms.
Dependency-based Convolutional Neural Networks for Sentence Embedding
In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies.
Open-Ended Visual Question-Answering
This thesis report studies methods to solve Visual Question-Answering (VQA) tasks with a Deep Learning framework.
Mapping Between fMRI Responses to Movies and their Natural Language Annotations
Several research groups have shown how to correlate fMRI responses to the meanings of presented stimuli.
UdL at SemEval-2017 Task 1: Semantic Textual Similarity Estimation of English Sentence Pairs Using Regression Model over Pairwise Features
natsheh/sensim
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SEMEVAL 2017
This paper describes the model UdL we proposed to solve the semantic textual similarity task of SemEval 2017 workshop.
EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity
epochx/emoatt
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WS 2017
In this paper we describe a deep learning system that has been designed and built for the WASSA 2017 Emotion Intensity Shared Task.
Concatenated Power Mean Word Embeddings as Universal Cross-Lingual Sentence Representations
UKPLab/arxiv2018-xling-sentence-embeddings
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Here, we generalize the concept of average word embeddings to power mean word embeddings.
