7 citations · 24 across the 17 of their papers we have counts for
7 papers · 1 filter
Unsupervised Video Summarization via Iterative Training and Simplified GAN
Hanqing Li, Diego Klabjan, Jean Utke
This paper introduces a new, unsupervised method for automatic video summarization using ideas from generative adversarial networks but eliminating the discriminator, having a simp…
Does Collaborative Human-LM Dialogue Generation Help Information Extraction from Human Dialogues?
Bo-Ru Lu, Nikita Haduong, Chia-Hsuan Lee +7
The capabilities of pretrained language models have opened opportunities to explore new application areas, but applications involving human-human interaction are limited by the fac…
S-Omninet: Structured Data Enhanced Universal Multimodal Learning Architecture
Ye Xue, Diego Klabjan, Jean Utke
Multimodal multitask learning has attracted an increasing interest in recent years. Singlemodal models have been advancing rapidly and have achieved astonishing results on various…
Early Classifying Multimodal Sequences
Alexander Cao, Jean Utke, Diego Klabjan
Often pieces of information are received sequentially over time. When did one collect enough such pieces to classify? Trading wait time for decision certainty leads to early classi…
A Policy for Early Sequence Classification
Alexander Cao, Jean Utke, Diego Klabjan
Sequences are often not received in their entirety at once, but instead, received incrementally over time, element by element. Early predictions yielding a higher benefit, one aims…
Gradient-Boosted Based Structured and Unstructured Learning
Andrea Treviño Gavito, Diego Klabjan, Jean Utke
We propose two frameworks to deal with problem settings in which both structured and unstructured data are available. Structured data problems are best solved by traditional machin…
Multi-Layer Attention-Based Explainability via Transformers for Tabular Data
Andrea Treviño Gavito, Diego Klabjan, Jean Utke
We propose a graph-oriented attention-based explainability method for tabular data. Tasks involving tabular data have been solved mostly using traditional tree-based machine learni…