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CNN deep learning-based image to vector depiction
In the computational science and engineering domains, the depiction of picture information remains an intricate problem. Such a description needs an...
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Taxonomy Enrichment with Text and Graph Vector Representation
Knowledge graphs such as DBpedia, Freebase or Wikidata always contain a taxonomic backbone that allows the arrangement and structuring of various...
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Unifying Lexical, Syntactic, and Structural Representations of Written Language for Authorship Attribution
Writing style in written language is a combination of consistent decisions associated with a specific author at different levels of language...
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The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot Transfer
Large multilingual language models such as mBERT or XLM-R enable zero-shot cross-lingual transfer in various IR and NLP tasks. Cao et al. [8]...
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Overcoming the Domain Gap in Neural Action Representations
Relating behavior to brain activity in animals is a fundamental goal in neuroscience, with practical applications in building robust brain-machine...
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GOWSeqStream: an integrated sequential embedding and graph-of-words for short text stream clustering
Recently, the proposed non-parametric Bayesian based techniques which aim to model short-length textual documents through the multinomial...
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Measuring Bias in a Ranked List Using Term-Based Representations
In most recent studies, gender bias in document ranking is evaluated with the NFaiRR metric, which measures bias in a ranked list based on an...
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Enhancing Table Retrieval with Dual Graph Representations
Table retrieval aims to rank candidate tables for answering natural language query, in which the most critical problem is how to learn informative...
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Comparing Bag of Words and TF-IDF with different models for hate speech detection from live tweets
Social media platforms such as Twitter have revolutionized online communication and interactions but often contain components of disdain for its...
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Vector Symbolic Architectures for Context-Free Grammars
Vector symbolic architectures (VSA) are a viable approach for the hyperdimensional representation of symbolic data, such as documents, syntactic...
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FreeStyler: A Free-Form Stylization Method via Multimodal Vector Quantization
Image stylization refers to the process of transforming an input image into a new one, while retaining its original content but in different styles....
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Adversarial Learning for Improved Patient Representations
In recent years, there has been an explosion in the amount of patient Electronic Health Records (EHR) made publicly available. This presents an...
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Preliminary Results of Group Detection Technique Based on User to Vector Encoding
This paper presents a novel approach for detecting groups of users based on observations of co-occurrences of user behavior. A Deep Neural Network is...
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Enhancing attributed network embedding via enriched attribute representations
Attributed network embedding enables to generate low-dimensional representations of network objects by leveraging both network structure and...
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Joint Optimization of Multi-vector Representation with Product Quantization
Dense retrieval models represent queries and documents with one or multiple fixed-width vectors and retrieve relevant documents via nearest neighbor...
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SoftQE: Learned Representations of Queries Expanded by LLMs
We investigate the integration of Large Language Models (LLMs) into query encoders to improve dense retrieval without increasing latency and cost,...
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Stacked convolutional auto-encoder representations with spatial attention for efficient diabetic retinopathy diagnosis
Recently, the attention mechanism has been effectively implemented in convolutional neural networks to boost performance of several computer vision...
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Coarse-to-Fine Entity Representations for Document-Level Relation Extraction
Document-level Relation Extraction (RE) requires extracting relations expressed within and across sentences. Recent works show that graph-based...
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Enhanced Graph Representations for Graph Convolutional Network Models
Graph Convolutional Network (GCN) is increasingly becoming popular among researchers for its capability of solving the task of classification of...
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Path homologies of motifs and temporal network representations
Path homology is a powerful method for attaching algebraic invariants to digraphs. While there have been growing theoretical developments on the...
