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Found 12 papers, 4 papers with code
Learning to Rank Visual Stories From Human Ranking Data
In this paper, we present the VHED (VIST Human Evaluation Data) dataset, which first re-purposes human evaluation results for automatic evaluation; hence we develop Vrank (VIST Ranker), a novel reference-free VIST metric for story evaluation.
Rethinking the Starting Point: Enhancing Performance and Fairness of Federated Learning via Collaborative Pre-Training
Most existing federated learning (FL) methodologies have assumed training begins from a randomly initialized model.
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation
Federated learning (FL) is a promising approach for solving multilingual tasks, potentially enabling clients with their own language-specific data to collaboratively construct a high-quality neural machine translation (NMT) model.
Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics
Traditional learning-based approaches to student modeling (e. g., predicting grades based on measured activities) generalize poorly to underrepresented/minority student groups due to biases in data availability.
Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning
To learn better representations of student activity, we augment our approach with a self-supervised behavioral pretraining methodology that leverages multiple modalities of student behavior (e. g., visits to lecture videos and participation on forums), and include a neural network attention mechanism in the model aggregation stage.
Let's Talk! Striking Up Conversations via Conversational Visual Question Generation
An engaging and provocative question can open up a great conversation.
Click-Based Student Performance Prediction: A Clustering Guided Meta-Learning Approach
Our methodology for predicting in-video quiz performance is based on three key ideas we develop.
Stretch-VST: Getting Flexible With Visual Stories
Therefore, we propose to {``}stretch{''} the stories, which create the potential to present in-depth visual details.
Plot and Rework: Modeling Storylines for Visual Storytelling
Writing a coherent and engaging story is not easy.
Ranked #27 on
Visual Storytelling
on VIST
MVIN: Learning Multiview Items for Recommendation
From the entity view, the mixing layer contrasts layer-wise GCN information to further obtain comprehensive features from internal entity-entity interactions in the KG.
Multi-step Joint-Modality Attention Network for Scene-Aware Dialogue System
Understanding dynamic scenes and dialogue contexts in order to converse with users has been challenging for multimodal dialogue systems.
GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model
Recently, researchers utilize Knowledge Graph (KG) as side information in recommendation system to address cold start and sparsity issue and improve the recommendation performance.
