Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Associative Learning01:27

Associative Learning

345
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
345
Stereotype Content Model02:16

Stereotype Content Model

14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Inductive Reasoning00:59

Inductive Reasoning

60.4K
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
60.4K
Surveys02:16

Surveys

14.8K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
14.8K
The Representativeness Heuristic02:13

The Representativeness Heuristic

15.8K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
15.8K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Elastic Multi-Gradient Descent for Parallel Continual Learning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Transcription factor EB as a therapeutic target for intracerebral hemorrhage: A review.

International journal of biological macromolecules·2026
Same author

Dual Domain-Attribute Learning Framework With Asynchronous Adapters for Continual Test-Time Adaptation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Causal Inference via Style Bias Deconfounding for Domain Generalization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Electron-Mediator-Free Microfluidic Photocatalytic Coenzyme Regeneration with 100% Conversion Efficiency within 126 S.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

C-NeRF: Representing Scene Changes as Directional Consistency Difference-Based NeRF.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026
Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026
Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Jun 28, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

548

Relation-Aware Heterogeneous Graph Network for Learning Intermodal Semantics in Textbook Question Answering.

Sai Zhang, Yunjie Wu, Xiaowang Zhang

    IEEE Transactions on Neural Networks and Learning Systems
    |April 23, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new method for textbook question answering (TQA) that effectively combines information from text and diagrams. The proposed intermodal relation-aware heterogeneous graph network (IMR-HGN) significantly improves answer extraction accuracy.

    More Related Videos

    Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
    08:32

    Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks

    Published on: September 5, 2019

    5.6K
    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
    07:36

    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

    Published on: November 30, 2018

    15.7K

    Related Experiment Videos

    Last Updated: Jun 28, 2025

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    548
    Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
    08:32

    Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks

    Published on: September 5, 2019

    5.6K
    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
    07:36

    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

    Published on: November 30, 2018

    15.7K

    Area of Science:

    • Artificial Intelligence
    • Natural Language Processing
    • Computer Vision

    Background:

    • Textbook Question Answering (TQA) requires integrating information from multiple modalities like text and diagrams.
    • Existing methods often process modalities independently, failing to capture crucial intermodal semantics.
    • A key challenge is bridging semantic gaps between modalities without losing individual modal information.

    Purpose of the Study:

    • To develop a novel approach for TQA that effectively extracts intermodal semantics.
    • To address the limitations of existing methods in handling multimodal information.
    • To improve the accuracy of answer inference in TQA tasks.

    Main Methods:

    • Proposed an intermodal relation-aware heterogeneous graph network (IMR-HGN) for TQA.
    • Introduced a multidomain consistent representation (MDCR) to align semantic features across modalities.
    • Implemented neighbor-based relation inpainting (NRI) to refine intermodal relationships.
    • Utilized hierarchical multisemantics aggregation (HMSA) with a reconstruction network (RN) for complete semantic extraction.

    Main Results:

    • The IMR-HGN model successfully extracted intermodal semantics for TQA.
    • Achieved a 2.16% improvement in accuracy on the TQA dataset's validation set.
    • Demonstrated a 3.04% increase in accuracy on the AI2D dataset's test set.

    Conclusions:

    • The proposed IMR-HGN effectively captures intermodal semantics, outperforming previous approaches.
    • This method offers a promising direction for enhancing multimodal understanding in AI.
    • The approach shows significant potential for improving educational tools and information retrieval systems.