Echoes of the Prior: A Computational Phenomenology of Forgetting
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Abstract (arXiv)
Memory is not merely the storage of data; it is the scaffolding of reality. When biological memory fades, the world does not simply turn black; it regresses into an unrecognizable chaos. Echoes of the Prior is an interactive installation that attempts to visualize this subjective phenomenology of forgetting. By inducing controlled synaptic decay within a Feed-Forward 3D Reconstruction model, we create an artistic analogy for the erosion of the brain's predictive priors. We position the Neural Network not as a tool for engineering, but as a cognitive proxy - a silicon brain whose structural degeneration evokes the disorienting, poetic, and terrifying experience of losing one's grip on the world. Ultimately, we offer this framework as a catalyst, inviting the wider community to explore the uncharted potential of neuromorphic aesthetics in visualizing the fragility of intelligence. Interactive demo see https://decart-4d.github.io/.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 48 references that are in the map. First posted on arXiv 10 Jun 2026.
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References · 9
- 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2021Vision Transformers for Dense Predictioncited by 1,803
- 2020Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hyperspherecited by 1,405
- 2024Grounded SAM: Assembling Open-World Models for Diverse Visual Taskscited by 929
- 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 692
- 2024MIDI: Multi-Instance Diffusion for Single Image to 3D Scene Generationcited by 117
- 2020Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Futurecited by 83
- 2020Learning to See: You Are What You Seecited by 4
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