activity
20242026
most citedDIPSER: A Dataset for In-Person Student Engagement Recognition in the Wild

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV2026

AIDEN: Design and Pilot Study of an AI Assistant for the Visually Impaired

Luis Marquez-Carpintero, Francisco Gomez-Donoso, Zuria Bauer +6

This paper presents AIDEN, an artificial intelligence-based assistant designed to enhance the autonomy and daily quality of life of visually impaired individuals, who often struggl…

cs.CV20261 cited

DIPSER: A Dataset for In-Person Student Engagement Recognition in the Wild

Luis Marquez-Carpintero, Sergio Suescun-Ferrandiz, Carolina Lorenzo Álvarez +4

In this paper, a novel dataset is introduced, designed to assess student attention within in-person classroom settings. This dataset encompasses RGB camera data, featuring multiple…

cs.CY2025

Simulating Students with Large Language Models: A Review of Architecture, Mechanisms, and Role Modelling in Education with Generative AI

Luis Marquez-Carpintero, Alberto Lopez-Sellers, Miguel Cazorla

Simulated Students offer a valuable methodological framework for evaluating pedagogical approaches and modelling diverse learner profiles, tasks which are otherwise challenging to…

cs.AI2025

AGENTiGraph: A Multi-Agent Knowledge Graph Framework for Interactive, Domain-Specific LLM Chatbots

Xinjie Zhao, Moritz Blum, Fan Gao +10

AGENTiGraph is a user-friendly, agent-driven system that enables intuitive interaction and management of domain-specific data through the manipulation of knowledge graphs in natura…

cs.CV2025

CADDI: An in-Class Activity Detection Dataset using IMU data from low-cost sensors

Luis Marquez-Carpintero, Sergio Suescun-Ferrandiz, Monica Pina-Navarro +2

The monitoring and prediction of in-class student activities is of paramount importance for the comprehension of engagement and the enhancement of pedagogical efficacy. The accurat…

cs.AI2024

AGENTiGraph: An Interactive Knowledge Graph Platform for LLM-based Chatbots Utilizing Private Data

Xinjie Zhao, Moritz Blum, Rui Yang +10

Large Language Models~(LLMs) have demonstrated capabilities across various applications but face challenges such as hallucination, limited reasoning abilities, and factual inconsis…