#self-supervised learning

topicself-supervised learning

35 papers · 1 filter

cs.CV2026

Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training?

Nusrat Munia, Tyler Ward, Nishat Nayla +2

The paper empirically compares pretraining‑finetuning and joint training of self‑supervised and supervised objectives across multiple SSL methods and vision tasks, showing that joi…

cs.IR2026

Learning to Forget: Satiation-Aware Long-Sequence Transducers for Mitigating Post-Purchase Redundancy

Yipin Dai, Ruocong Tang, Xing Fang +4

The paper introduces a satiation-aware framework for sequential recommendation that detects when a purchase satisfies a user’s intent and temporarily suppresses related items, then…

cs.IR2026

Adaptive Fusion Self-supervised Learning for Recommendation

Yu Zhang, Lei Sang, Yi Zhang +2

The paper proposes Adaptive Fusion Graph Contrastive Learning (AFGCL), a self‑supervised recommendation method that avoids costly graph augmentations by fusing representations from…

eess.IV2026

HPC-Enabled Video-based Coastal Wave Parameter Estimation Using V-JEPA and Deep Spatiotemporal Learning

Abubakar Hamisu Kamagata, Dharm Singh Jat, Attlee Munyaradzi Gamundani +3

The paper introduces an HPC‑enabled deep learning system that estimates five coastal wave parameters from monocular video using a self‑supervised ViT backbone, dual‑stream temporal…

cs.LG2026

DiffEEG: A Self-Supervised Denoising Diffusion Model for Learning EEG Generic Representations

Abdulkader Helwan, Lina Abou-Abbas, Hussein El Amouri +2

The paper introduces DiffEEG, a self‑supervised diffusion model that learns generic EEG representations from millions of unlabeled recordings and fine‑tunes them with reinforcement…

cs.SD2026

Evidence Subspace Projection: Measuring How Much Evidence Explains Deepfake Detection in Self-Supervised Speech Models

Yixuan Xiao, Cheng-Wei Lin, Xin Wang +5

The paper introduces Evidence Subspace Projection, a technique that quantifies how different evidence factors (like attack type, codec, gender, transmission) explain the decisions…