Sentence Embedding
132 papers with code • 0 benchmarks • 7 datasets
Benchmarks
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Libraries
Use these libraries to find Sentence Embedding models and implementations
Tatoeba
UR-FUNNY
Video2GIF
Latest papers
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.
Sentence-level Media Bias Analysis with Event Relation Graph
yuanyuanlei-nlp/sentence_level_media_bias_naacl_2024
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Then, we incorporate event relation graph for bias sentences identification in two steps: an event-aware language model is built to inject the events and event relations knowledge into the basic language model via soft labels; further, a relation-aware graph attention network is designed to update sentence embedding with events and event relations information based on hard labels.
SentiCSE: A Sentiment-aware Contrastive Sentence Embedding Framework with Sentiment-guided Textual Similarity
nayohan/senticse
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However, they neglect to evaluate the quality of their constructed sentiment representations; they just focus on improving the fine-tuning performance, which overshadows the representation quality.
KDMCSE: Knowledge Distillation Multimodal Sentence Embeddings with Adaptive Angular margin Contrastive Learning
Previous work on multimodal sentence embedding has proposed multimodal contrastive learning and achieved promising results.
Making Sentence Embeddings Robust to User-Generated Content
NLP models have been known to perform poorly on user-generated content (UGC), mainly because it presents a lot of lexical variations and deviates from the standard texts on which most of these models were trained.
Bridging Language and Items for Retrieval and Recommendation
This paper introduces BLaIR, a series of pretrained sentence embedding models specialized for recommendation scenarios.
UMBCLU at SemEval-2024 Task 1A and 1C: Semantic Textual Relatedness with and without machine translation
The aim of SemEval-2024 Task 1, "Semantic Textual Relatedness for African and Asian Languages" is to develop models for identifying semantic textual relatedness (STR) between two sentences using multiple languages (14 African and Asian languages) and settings (supervised, unsupervised, and cross-lingual).
Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning
jeongwoopark0514/morality-is-non-binary
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Our results show that a pluralist approach to morality can be captured in an embedding space.
Some Like It Small: Czech Semantic Embedding Models for Industry Applications
seznam/czech-semantic-embedding-models
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Ultimately, this article presents practical applications of the developed sentence embedding models in Seznam. cz, the Czech search engine.
An Efficient Self-Supervised Cross-View Training For Sentence Embedding
mrpeerat/sct
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In this paper, we propose a framework called Self-supervised Cross-View Training (SCT) to narrow the performance gap between large and small PLMs.
