Pith. sign in

REVIEW 1 cited by

LSDvis: Hallucinatory Data Visualisations in Real World Environments

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2312.11144 v1 pith:F7KM5OTK submitted 2023-12-18 cs.HC

classification cs.HC
keywords lsdvisvisualisationsdataconceptenvironmentenvironmentshallucinatoryproof
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We propose the concept of "LSDvis": the (highly exaggerated) visual blending of situated visualisations and the real-world environment to produce data representations that resemble hallucinations. Such hallucinatory visualisations incorporate elements of the physical environment, twisting and morphing their appearance such that they become part of the visualisation itself. We demonstrate LSDvis in a ``proof of proof of concept'', where we use Stable Diffusion to modify images of real environments with abstract data visualisations as input. We conclude by discussing considerations of LSDvis. We hope that our work promotes visualisation designs which deprioritise saliency in favour of quirkiness and ambience.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SceneLoom: Communicating Data with Scene Context

    cs.HC 2025-07 conditional novelty 6.0 of 10

    SceneLoom guides a vision-language model through a design space derived from 54 data videos to generate chart-in-image designs aligned with user narrative intent.

Pith tools