Probing JEPA Latent Spaces Against Simulated Ground Truth: Fidelity, Sufficiency, and Linguistic Properties

Probes are used to claim that a representation encodes a property, but a probe that succeeds may reflect its own capacity rather than the representation. We study probing of JEPA latent spaces with two controls: simulated systems with known state, where a probe's fidelity can be measured exactly, and linguistic properties (negation, tense, and syntactic depth) with matched control tasks. A pilot with a random encoder shows selectivity that grows with width; the JEPA probing results are pending. Preprint. Results in this version come from small-scale pilot experiments; the full experimental protocol is described in the text and is pending.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-02
DOI
https://doi.org/10.5281/zenodo.23890667
Primary Topic
Topic Modeling
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Probing JEPA Latent Spaces Against Simulated Ground Truth: Fidelity, Sufficiency, and Linguistic Properties

Dheiver Francisco Santos
Zenodo (CERN European Organization for Nuclear Research)
Topic Modeling
preprint

Probing JEPA Latent Spaces Against Simulated Ground Truth: Fidelity, Sufficiency, and Linguistic Properties

Dheiver Francisco Santos
preprint en

Abstract

Probes are used to claim that a representation encodes a property, but a probe that succeeds may reflect its own capacity rather than the representation. We study probing of JEPA latent spaces with two controls: simulated systems with known state, where a probe's fidelity can be measured exactly, and linguistic properties (negation, tense, and syntactic depth) with matched control tasks. A pilot with a random encoder shows selectivity that grows with width; the JEPA probing results are pending. Preprint. Results in this version come from small-scale pilot experiments; the full experimental protocol is described in the text and is pending.

Zenodo (CERN European Organization for Nuclear Research)
Topic Modeling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon