129,938 Result(s)
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Chapter
Transformer-Driven Models for Language, Vision, and Multimodality
In this chapter, we will learn about the modeling and learning techniques that drive multimodal applications. We will focus specifically on the recent advances in transformer-based modeling for natural languag...
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Chapter
Multimodal Content Generation
In this chapter, we will review the advances that are being made in this new field of multimodal content generation and also discuss several challenges associated with this emerging technology. First, we will ...
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Chapter
Outlook
While multimodal information retrieval has several exciting applications and a high potential for impact on important problems, there are several challenges associated with the information that lives on the in...
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Chapter
Introduction
In this book, our emphasis is on multimodal information retrieval, specifically concentrating on text and image data. The traditional unimodal systems, limited to a single type of data, often fall short of cap...
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Chapter
Multimodal Information Retrieval
In today’s rapidly evolving digital landscape, the wealth of available information has expanded beyond the boundaries of traditional text-based content. With the proliferation of multimedia platforms and data ...
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Chapter
Retrieval Augmented Modeling
Till this point in our book, we have discussed the fundamental principles of information retrieval, exploring its key elements, and various approaches to achieving effective retrieval, including multimodal ret...
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Chapter and Conference Paper
Exploring the Nexus Between Retrievability and Query Generation Strategies
Quantifying bias in retrieval functions through document retrievability scores is vital for assessing recall-oriented retrieval systems. However, many studies investigating retrieval model bias lack validation...
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Chapter and Conference Paper
Deep Learning for Journalism: The Bibliometric Analysis of Deep Learning for News Production in the Artificial Intelligence Era
This research aims to evaluate the articles published from 2018 to 2023. We focused on the deep learning issues that have risen in the last decade. Deep learning is the popular approach in news research, espec...
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Chapter
Computer Network Security Fundamentals
In this chapter, we give a general definition of the state of security in any environment and then localize this security concept in a computer network. In doing this, the chapter focuses on the computer netwo...
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Chapter and Conference Paper
An Industrial Experience Leveraging the iv4XR Framework for BDD Testing of a 3D Sandbox Game
Industrial-grade games, like Space Engineers, must adopt swift development and testing processes to conform to rigorous quality standards. Nevertheless, the testing phase of these extensive and complex games h...
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Chapter and Conference Paper
Absolute Variation Distance: An Inversion Attack Evaluation Metric for Federated Learning
Federated Learning (FL) has emerged as a pivotal approach for training models on decentralized data sources by sharing only model gradients. However, the shared gradients in FL are susceptible to inversion att...
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Chapter and Conference Paper
GraphSAGE-Based Spammer Detection Using Social Attribute Relationship
Spammers have existed since the birth of the Internet. They constantly pollute the social network environment, seriously degrade user experience and pose a threat to user account security. Finding spammers has...
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Chapter and Conference Paper
BertPE: A BERT-Based Pre-retrieval Estimator for Query Performance Prediction
Query Performance Prediction (QPP) aims to estimate the effectiveness of a query in addressing the underlying information need without any relevance judgments. More recent works in this area have employed the ...
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Chapter and Conference Paper
Paraphrasers and Classifiers: Controllable Text Generation for Text Style Transfer
Text style transfer (TST) is an NLP task with a long history and a broad range of applications. Recently, it has seen success with the use of large pretrained language models (LMs). However, the size of contem...
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Chapter and Conference Paper
Navigating Uncertainty: Optimizing API Dependency for Hallucination Reduction in Closed-Book QA
While Large Language Models (LLM) are able to accumulate and restore knowledge, they are still prone to hallucination. Especially when faced with factual questions, LLM cannot only rely on knowledge stored in ...
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Chapter and Conference Paper
DQN-Based Applications Offloading with Multiple Interdependent Tasks in Mobile Edge Computing
Recently, Vehicular Edge Computing (VEC) is evolving as a solution for offloading computationally intensive tasks in in-vehicle environments. However, when the number of vehicles and users is large, pure edge ...
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Chapter and Conference Paper
CHIP 2023 Task Overview: Complex Information and Relation Extraction of Drug-Related Materials
Drug labels or package insert are legal documents that include significant information and are highly valuable. However, it contains both structured and unstructured information, which is challenging to extrac...
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Chapter and Conference Paper
Beyond Topicality: Including Multidimensional Relevance in Cross-encoder Re-ranking
In this paper, we propose a novel approach to consider multiple dimensions of relevance in cross-encoder re-ranking. On the one hand, cross-encoders constitute an effective solution for re-ranking when conside...
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Chapter and Conference Paper
Biomedical Relation Extraction via Syntax-Enhanced Contrastive Networks
Extracting biomedical relations from biomedical literature automatically is essential for discovering new biomedical knowledge. However, in the biomedical domain, some texts with different types have semantic ...
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Chapter and Conference Paper
A Streaming Approach to Neural Team Formation Training
Predicting future successful teams of experts who can effectively collaborate is challenging due to the experts’ temporality of skill sets, levels of expertise, and collaboration ties, which is overlooked by prio...
