text similarity
69 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in text similarity
Datasets
DICE: a Dataset of Italian Crime Event news
Most implemented papers
Extensive Self-Contrast Enables Feedback-Free Language Model Alignment
In this work, we introduce Self-Contrast, a feedback-free large language model alignment method via exploiting extensive self-generated negatives.
Deep Generative Model for Joint Alignment and Word Representation
uva-slpl/embedalign
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NAACL 2018
This work exploits translation data as a source of semantically relevant learning signal for models of word representation.
Large-Scale Cover Song Detection in Digital Music Libraries Using Metadata, Lyrics and Audio Features
In this work, we investigate whether textual music information (such as metadata and lyrics) can be used along with audio for large-scale cover identification problem in a wide digital music library.
Using Sentiment Induction to Understand Variation in Gendered Online Communities
We analyze gendered communities defined in three different ways: text, users, and sentiment.
Automating the search for a patent's prior art with a full text similarity search
helmersl/patent_similarity_search
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The evaluation results show that our automated approach, besides accelerating the search process, also improves the search results for prior art with respect to their quality.
Evaluation of Scientific Elements for Text Similarity in Biomedical Publications
Rhetorical elements from scientific publications provide a more structured view of the document and allow algorithms to focus on particular parts of the text.
Fake Review Detection Using Behavioral and Contextual Features
We empirically proved importance of selected feature set for classification model to identify fake reviews.
Text classification with word embedding regularization and soft similarity measure
In our work, we investigate the individual and joint effect of the two word embedding regularization techniques on the document processing speed and the task performance of the SCM and the WMD on text classification.
An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining
Multi-task learning (MTL) has achieved remarkable success in natural language processing applications.
