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Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution
May 25, 2026Zixin Jessie Chen, Zhuo Chen, Archer Wang +4Super-Resolution Framework Large-Scale Image Generation
STORM: Internalized Modeling for Spatial-Temporal Reasoning in Video-Language Models
May 25, 2026Yiming Liang, Yixiao Chen, Yiyang Zhou +8Video-Language Models Video Understanding
LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence
May 25, 2026Xiang An, Yin Xie, Feilong Tang +27Video Understanding Vision Encoders
LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data
May 25, 2026Knut Peterson, Zaid Mayers, Azmain Yousuf +5Unmanned Aerial Vehicle Detection Aerial Dataset
Explore Before You Solve: The Speed--Depth Trade-off in Epistemic Agents for ARC-AGI-3
May 25, 2026Liew Keong HanAgentic Benchmarks Efficient Exploration
Mitigating Provenance-Role Collapse in Long-Term Agents via Typed Memory Representation
May 25, 2026Zhengda Jin, Bingbing Wang, Jing Li +2Agent Memory Long-Term Memory
Geometric Evolution Maps: Extracting Stable Concept Probes from Transformer Residual Streams
May 25, 2026James HenryTransformer Residual Streams Handoff
Modeling Dynamic Mixtures of Time-Delay Systems from Streaming Time Series
May 25, 2026Ren Fujiwara, Yasuko Matsubara, Yasushi SakuraiDelay Mixture Models
Evaluating passing decision-making in professional football: An enhanced MPNN approach to Receiver Selection
May 25, 2026Gabriel Masella, Giuseppe Alessio D'Inverno, Max Goldsmith +1Message Passing Neural Networks Graph Neural Networks
Phantom transitions in language model fine-tuning
May 25, 2026Vaibhav Prakash, Jayasri DontabhaktuniLarge Language Model Fine-Tuning Finetuning
Opportunistic Target Selection: Early Directional Commitment for Query-Efficient Black-Box Adversarial Attacks
May 25, 2026Florent Tariolle, Florian YgerAdversarial Examples Time-Step-Wise Learnable Surrogate Gradient Function
Closed-Form Node Classification with Exact Graph Unlearning
May 25, 2026Aditya Gaur, Charu SharmaGraph Neural Networks Propagation
SPIN: Decentralized Swarm Control via Tensorized Policy Coordination
May 25, 2026Zhaowen FanSwarms Neural Control
From Simulation to Enaction: Post-trained language models recognize and react to their own generations
May 25, 2026Asvin G., Jack LindseyLarge Language Model Post-Training Surprisal
PitchBench: Measuring Pitch Hearing in Audio-Language Models
May 25, 2026Milan Liessens Dujardin, Song-Ze Yu, Craver Corbyn Thomas-Smith +2Large Audio Language Models Pitch
AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writing
May 25, 2026Thomas Stephan JuzekCross-Lingual Consistency Lexicon
Tool-Call Dependency Structure is Linearly Decodable in LLM Agent Residual Streams
May 25, 2026Tianda Sun, Dimitar KazakovDependency Graph Large Language Model Agents
A Principled Self-Referenced Early Stopping Approach for Deep Image Prior
May 24, 2026Chaoyan Huang, Cheng-Han Huang, Ismail R. Alkhouri +1Ill-Posed Inverse Problem Gaussian Noise
Whose Alignment? Comparing LLM Process Alignment Across Diverse Organizational Decision Contexts
May 24, 2026Niklas Weller, Emilio BarkettLarge Language Model Alignment Pluralistic Alignment
Aligning Cellular Sheaves with Classifier Attention for Interpretable Weakly-Supervised Pathology Localization
May 24, 2026Devansh Lalwani, Swapnil Bhat, Maulik ShahWhole-Slide Images Multiple Instance Learning
STREAM: A Data-Centric Framework for Mining High-Value Task-Oriented Dialogues from Streaming Media
May 24, 2026Liang Xue, Haoyu Liu, Cheng Wang +3Conversational Datasets Dialogue
Courant: a State-Adaptive Perceiver-Based Neural Surrogate with Local Support and Interpretable Field Decomposition
May 24, 2026Anuj Kumar, Josiah Bjorgaard, Nikolaos Bouklas +2Surrogate Models Neural Partial Differential Equation Solvers
Reinforcement Learning with a Bilevel World-Model Architecture for Scan-Order Optimisation in Laser Directed Energy Deposition
May 24, 2026Xian Wu, Haoran Li, Yuanqi Chu +2Sequential Decision Making Data Generation
Cross-Domain Generalization Limits of Vision Foundation Models in Facial Deepfake Detection
May 24, 2026Ibrahim DelibasogluExplainable Deepfake Detection Vision Foundation Models
T2S-MPC: Time-Embedded Online Adaptive Model Predictive Control for Time-Varying Dynamics
May 24, 2026Zeyu Shen, Zhuoyuan Wang, Laixi ShiModel Predictive Control Time-Varying Systems
Time Segmented Beamforming via Dynamic Programming: Theory and Implementation
May 24, 2026Manan Mittal, Ryan M. Corey, Diego Cuji +2Beamforming Interference
Manifold-Constrained MPPI: Real-Time Sampling-Based Control Under Hard Constraints
May 24, 2026Seulchan Lee, Sanghyun KimModel Predictive Path Integral Robotic Arms
How Noisy Poses Break Inverse Dynamics: Analysis and Mitigation for Video-Based Joint Torque Estimation
May 23, 2026Donghyun Kim, Chanyoung Kim, Eunseo Jeong +2Inverse Dynamics Parametric Body Models
Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction
May 23, 2026Simon Dennis, Kevin Shabahang, Hao Guo +1LLM Inference Efficiency Consolidation
Silent Failures in Physical AI: A Literature Review of Runtime Action Authorization for Autonomous Systems
May 23, 2026Barak OrRuntime Enforcement Artificial Intelligence Safety

May 25, 2026 · cs.CVJ/K move · Enter open · S save

Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution

Zixin Jessie Chen, Zhuo Chen, Archer Wang, Jeff Gore+3

Department of Physics, Massachusetts Institute of Technology · NSF AI Institute for Artificial Intelligence and Fundamental Interactions · Institute for Data, Systems and Society, Massachusetts Institute of Technology · Department of EECS, Massachusetts Institute of Technology

Creating images from noise is image generation; reconstructing fine details from coarse inputs is super-resolution. Despite their practical differences, both can be understood as reversing information loss across scales. We introduce

\textbf{SKILD}

, a

\textbf{S}

cale-invariant

\textbf{K}

-Space

\textbf{I}

mage

\textbf{L}

earning

\textbf{D}

iffusion model that unifies generation and continuous super-resolution within a single unconditional framework. Both natural images and critical physical systems exhibit scale invariance, and we leverage it to design a forward process that attenuates image content from fine to coarse scales while injecting spectrum-matched Gaussian noise, making scale an explicit coordinate of the diffusion dynamics. The same trained reverse process performs generation and continuous super-resolution by varying only the starting timestep:

\textit{no task-specific architecture, no conditioning branch, no classifier-free guidance, no retraining per scale factor}

. Empirically, SKILD reaches FID

2.65

and Inception Score

9.63

on unconditional CIFAR-10, performs

2\times

8\times

super-resolution on ImageNet from a single unconditional checkpoint while outperforming conditional models across perceptual metrics, and reconstructs critical Ising models whose connected four-point correlations closely track the ground truth.

Super-Resolution Framework Large-Scale Image Generation Imagenet Scaling Laws Skillaudit

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