Prospective role of foundation models in advancing autonomous vehicles

J Wu, B Gao, J Gao, J Yu, H Chu, Q Yu, X Gong… - Research, 2024 - spj.science.org
With the development of artificial intelligence and breakthroughs in deep learning, large-
scale foundation models (FMs), such as generative pre-trained transformer (GPT), Sora, etc …

Unified Approaches in Self-Supervised Event Stream Modeling: Progress and Prospects

L Zólyomi, T Wang, S Ennadir, O Smirnov… - arxiv preprint arxiv …, 2025 - arxiv.org
The proliferation of digital interactions across diverse domains, such as healthcare, e-
commerce, gaming, and finance, has resulted in the generation of vast volumes of event …

T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data

H Thimonier, JLDM Costa, F Popineau… - arxiv preprint arxiv …, 2024 - arxiv.org
Self-supervision is often used for pre-training to foster performance on a downstream task by
constructing meaningful representations of samples. Self-supervised learning (SSL) …

A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective

Z Zhao, Y Su, Y Li, Y Zou, R Li, R Zhang - arxiv preprint arxiv:2403.16137, 2024 - arxiv.org
Graph self-supervised learning (SSL) is now a go-to method for pre-training graph
foundation models (GFMs). There is a wide variety of knowledge patterns embedded in the …

Graphs, Geometry, and Learning Representations: Navigating the Non-Euclidean Landscape in Computer Vision and Beyond

G Skenderi - 2024 - iris.univr.it
Artificial Intelligence (AI) requires machines capable of learning and generalizing from data
without being explicitly programmed to do so, giving rise to the field of Machine Learning …