Search Results for author:
Found 11 papers, 1 papers with code
LLaVA-Docent: Instruction Tuning with Multimodal Large Language Model to Support Art Appreciation Education
This study explores the application of multi-modal large language models (MLLMs) in art appreciation education, focusing on developing LLaVA-Docent, a model that leverages these advancements.
Difficulty-Focused Contrastive Learning for Knowledge Tracing with a Large Language Model-Based Difficulty Prediction
This paper presents novel techniques for enhancing the performance of knowledge tracing (KT) models by focusing on the crucial factor of question and concept difficulty level.
MonaCoBERT: Monotonic attention based ConvBERT for Knowledge Tracing
Models that consider both interpretability and the performance improvement have been insufficient.
Imagine Networks
In this paper, we introduce an imagine network that can simulate itself through artificial association networks.
Memory Association Networks
We introduce memory association networks(MANs) that memorize and remember any data.
Deductive Association Networks
we introduce deductive association networks(DANs), a network that performs deductive reasoning.
All-In-One: Artificial Association Neural Networks
Further, we propose a new neural data structure that can express all basic models of existing neural networks in a tree structure.
Graph Tree Neural Networks
Instead of using fixed sequence layers, we create a GT for each data and train GTNN according to the tree's structure.
Pixab-CAM: Attend Pixel, not Channel
To understand the internal behaviors of convolution neural networks (CNNs), many class activation mapping (CAM) based methods, which generate an explanation map by a linear combination of channels and corresponding weights, have been proposed.
Adullam at SemEval-2017 Task 4: Sentiment Analyzer Using Lexicon Integrated Convolutional Neural Networks with Attention
We propose a sentiment analyzer for the prediction of document-level sentiments of English micro-blog messages from Twitter.
