CI-JEPA: A Counterfactual Analysis of Latent Representations in Joint-Embedding Predictive Architectures for Self-Supervised Learning

arXiv:2610.05043 · cs.AI · Submitted 2026-10-04 · Read on arXiv

cs.AI

Submitted: 2026-10-04

Updated: 2026-10-04

Comments: This article has been accepted for the International Symposium on Smart Systems, Algorithms & Applications 2026 (IS3A3 2026), Tezpur Central University, India

Journal ref: International Symposium on Smart Systems, Algorithms & Applications 2026 (IS3A3 2026), Tezpur Central University, India

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes

Sources

• Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
• Noise or Signal: The Role of Image Backgrounds in Object Recognition
• Interventional Causal Representation Learning
• Understanding intermediate layers using linear classifier probes

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