Buchumschlag

Quantifying the Academic Quality of Children's Videos using Machine Comprehension

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Kumar, Sumeet, T., Mallikarjuna, Khudabukhsh, Ashiqur
Format:	Preprint
Veröffentlicht:	2023
Schlagworte:	Computers and Society
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Global Patterns in Student Stress and Academic Performance: A Machine Learning Study Using PISA 2022
von: Ghazanchyan, Ani, et al.
Veröffentlicht: (2026)

Down the Toxicity Rabbit Hole: A Novel Framework to Bias Audit Large Language Models
von: Dutta, Arka, et al.
Veröffentlicht: (2023)

Gender Representation and Bias in Indian Civil Service Mock Interviews
von: Banerjee, Somonnoy, et al.
Veröffentlicht: (2024)

Cutting through the noise to motivate people: A comprehensive analysis of COVID-19 social media posts de/motivating vaccination
von: Rahman, Ashiqur, et al.
Veröffentlicht: (2024)

Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive
von: Weerasooriya, Tharindu Cyril, et al.
Veröffentlicht: (2023)

Investigating Vaccine Buyer's Remorse: Post-Vaccination Decision Regret in COVID-19 Social Media Using Politically Diverse Human Annotation
von: Stanley, Miles, et al.
Veröffentlicht: (2026)

Quality of Coverage (QoC): Quantifying Cellular Network Coverage Quality, Usability and Stability
von: Srinivasavaradhan, Varshika, et al.
Veröffentlicht: (2025)

Public interest in science or bots? Selective amplification of scientific articles on Twitter
von: Rahman, Ashiqur, et al.
Veröffentlicht: (2024)

Hope vs. Hate: Understanding User Interactions with LGBTQ+ News Content in Mainstream US News Media through the Lens of Hope Speech
von: Pofcher, Jonathan, et al.
Veröffentlicht: (2025)

Community Needs and Assets: A Computational Analysis of Community Conversations
von: Chowdhury, Md Towhidul Absar, et al.
Veröffentlicht: (2024)

Content and Quality Analysis of Parent-Facing Applications for Feeding Children with Autism Spectrum Disorder
von: Kuzagbe, Christopher Cofie, et al.
Veröffentlicht: (2025)

The Compute Divide in Machine Learning: A Threat to Academic Contribution and Scrutiny?
von: Besiroglu, Tamay, et al.
Veröffentlicht: (2024)

Quantifying the influence of Vocational Education and Training with text embedding and similarity-based networks
von: Lee, Hyeongjae, et al.
Veröffentlicht: (2025)

What About the Scene with the Hitler Reference? HAUNT: A Framework to Probe LLMs' Self-consistency Via Adversarial Nudge
von: Dutta, Arka, et al.
Veröffentlicht: (2025)

Quantifying the Persona Effect in LLM Simulations
von: Hu, Tiancheng, et al.
Veröffentlicht: (2024)

Quantifying Itch and its Impact on Sleep Using Machine Learning and Radio Signals
von: Ouroutzoglou, Michail, et al.
Veröffentlicht: (2025)

Quantifying the Persistence of Daily Routines
von: Luong, Nguyen, et al.
Veröffentlicht: (2026)

Infrastructure Ombudsman: Mining Future Failure Concerns from Structural Disaster Response
von: Chowdhury, Md Towhidul Absar, et al.
Veröffentlicht: (2024)

Video-based Social Interaction Behavior Analysis with the Simulated Interaction Task for Children (Kids-SIT)
von: Pardhi, Rituja, et al.
Veröffentlicht: (2026)

Quantifying Gender Biases Towards Politicians on Reddit
von: Marjanovic, Sara, et al.
Veröffentlicht: (2021)

The Quantified Body: Identity, Empowerment, and Control in Smart Wearables
von: Wang, Maijunxian
Veröffentlicht: (2025)

Research on Education Big Data for Students Academic Performance Analysis based on Machine Learning
von: Wang, Chun, et al.
Veröffentlicht: (2024)

The Cognitive Kardashev Scale: Quantifying the Material Envelope of Civilisational Computation
von: Sharma, Sachin
Veröffentlicht: (2026)

In Memorium: The Academic Journal
von: Beale, Russell
Veröffentlicht: (2025)

Using Machine Learning in Analyzing Air Quality Discrepancies of Environmental Impact
von: Wang, Shuangbao Paul, et al.
Veröffentlicht: (2025)

Evaluation of Machine Learning Models in Student Academic Performance Prediction
von: Sandeepa, A. G. R., et al.
Veröffentlicht: (2025)

Better Together: Quantifying the Benefits of AI-Assisted Recruitment
von: Aka, Ada, et al.
Veröffentlicht: (2025)

Quantifying the Risk of Pastoral Conflict in 4 Central African Countries
von: Solaa, Lirika, et al.
Veröffentlicht: (2024)

Quantifying Privacy Risks of Public Statistics to Residents of Subsidized Housing
von: Steed, Ryan, et al.
Veröffentlicht: (2024)

Early Results from Teaching Modelling for Software Comprehension in New-Hire Onboarding
von: Kumar, Mrityunjay, et al.
Veröffentlicht: (2025)

Quantifying Polarization: A Comparative Study of Measures and Methods
von: Di Martino, Edoardo, et al.
Veröffentlicht: (2025)

Maturity Framework for Enhancing Machine Learning Quality
von: Castelli, Angelantonio, et al.
Veröffentlicht: (2025)

Trade-offs Between Individual and Group Fairness in Machine Learning: A Comprehensive Review
von: Benítez-Peña, Sandra, et al.
Veröffentlicht: (2026)

Automated Assessment of Students' Code Comprehension using LLMs
von: Oli, Priti, et al.
Veröffentlicht: (2023)

Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale
von: Wang, Xinlei, et al.
Veröffentlicht: (2026)

Quantifying Gender Stereotypes in Japan between 1900 and 1999 with Word Embeddings
von: Sakai, Shintaro, et al.
Veröffentlicht: (2025)

Novel Topological Machine Learning Methodology for Stream-of-Quality Modeling in Smart Manufacturing
von: Lee, Jay, et al.
Veröffentlicht: (2024)

Quantifying Media Influence on Covid-19 Mask-Wearing Beliefs
von: Rabb, Nicholas, et al.
Veröffentlicht: (2024)

Quantifying the Vulnerabilities of the Online Public Square to Adversarial Manipulation Tactics
von: Truong, Bao Tran, et al.
Veröffentlicht: (2019)

Detecting AI-Generated Text in Educational Content: Leveraging Machine Learning and Explainable AI for Academic Integrity
von: Najjar, Ayat A., et al.
Veröffentlicht: (2025)