PRISM
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Related Articles from SNS
Wave-optical formulation of the image-rotation property in Dove prisms: A Fourier-optics approach
arXiv:2606.05027v1 Announce Type: new Abstract: In this paper, we present a formula for calculating the complex amplitude of the output electric field for a given input wave that impinges on a Dove prism. We use Fourier optics to decompose the input wave into plane waves, then find the output plane waves of the Dove prism as functions of the spatial frequencies of the input components. The total output image is then obtained by integrating all the output plane waves, resulting in a final...
PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design
arXiv:2605.26502v2 Announce Type: replace Abstract: The inverse problem of multilayer thin-film optical coatings design represents a complex combinatorial-continuous optimization challenge. We present PRISM (Position-encoded Regressive Inverse Spectral Model), a unified decoder-only autoregressive transformer that streamlines this process by jointly predicting discrete material selection and continuous thickness regression within a single backbone. PRISM introduces two primary architectural...
PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design
arXiv:2605.26502v2 Announce Type: replace-cross Abstract: The inverse problem of multilayer thin-film optical coatings design represents a complex combinatorial-continuous optimization challenge. We present PRISM (Position-encoded Regressive Inverse Spectral Model), a unified decoder-only autoregressive transformer that streamlines this process by jointly predicting discrete material selection and continuous thickness regression within a single backbone. PRISM introduces two primary...
PRISM: Progressive Reasoning through Iterative Slot Memory for Vision
Announce Type: new Abstract: Modern vision models process images in a single feed-forward pass, which limits their ability to recover missing evidence or refine uncertain representations under incomplete observations. Inspired by the iterative nature of human perception, we introduce PRISM (Progressive Reasoning through Iterative Slot Memory), a pyramid vision architecture that reasons over images through iterative refinement. At a high level, PRISM groups visual features into object-centric...
Ground-state phase diagram of Rydberg atoms in a triangular-prism array
arXiv:2606.01116v1 Announce Type: cross Abstract: We study the ground-state phase diagram of Rydberg atoms in a triangular-prism optical tweezer array using the density matrix renormalization group. By tuning the detuning-to-Rabi-frequency ratio and the Rydberg blockade radius, the system realizes several density-wave phases with spontaneous breaking of translational and leg-exchange symmetries. Unlike two-leg Rydberg ladders with $\mathbb{Z}_2$ leg-exchange symmetry, the triangular prism...
PRISM: Rethinking Atmospheric Scattering Reconstruction as a Unified Understanding and Restoration Model for Real-world Dehazing
arXiv:2604.07048v2 Announce Type: replace Abstract: Real-world image dehazing (RID) aims to remove haze-induced degradation from real scenes. This task remains challenging due to non-uniform haze distribution, spatially varying color shifts, and the scarcity of paired real hazy-clean data. In PRISM, we propose Proximal Scattering Atmosphere Reconstruction (PSAR), a physically structured framework that jointly reconstructs the clear scene and scattering variables under the atmospheric...
PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization
Announce Type: new Abstract: Unifying the complementary strengths of diverse Vision Foundation Models (VFMs) into a single efficient model is highly desirable but challenged by the negative transfer inherent in monolithic distillation. To address these feature conflicts, we introduce \textbf{PRISM}, a novel dual-stream Mixture-of-Experts (MoE) framework that synergizes VFMs via modular specialization.
PRISM: PRior-guided Imagination Sampling in world Models
Announce Type: new Abstract: A learned world model provides a powerful physical intuition for evaluating future states. But its effectiveness in continuous control also depends critically on how candidate actions are generated for model-based planning. Rather than solely asking how accurately a model can simulate the future, we ask: which candidate actions are worth evaluating in the first place?
PRISM: Preference-Aware Influence Function Based Data Selection Method for Efficient Fine-Tuning
arXiv:2605.21422v3 Announce Type: replace Abstract: As LLMs continue to scale up, improving training efficiency heavily relies on effective data utilization. Data selection mitigates this issue by allocating the limited training budget to high-value examples that optimally facilitate the model's target behavior. Most existing approaches define target behavior via a set of target examples and score candidate training data based on their estimated influence on these samples.
PRISM: Preference-Aware Influence Function Based Data Selection Method for Efficient Fine-Tuning
Announce Type: replace Abstract: As LLMs continue to scale up, improving training efficiency heavily relies on effective data utilization. Data selection mitigates this issue by allocating the limited training budget to high-value examples that optimally facilitate the model's target behavior. Most existing approaches define target behavior via a set of target examples and score candidate training data based on their estimated influence on these samples.