Reasoning-Informed Visual Editing

arXiv:2610.12343 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Code: https://github.com/VisionXLab/RISEBench

Terminology

• Consistency — 70× in this paper · explained in 3 episodes
• Instruction Reasoning — 50× in this paper
• Appearance Consistency — 42× in this paper
• Visual Plausibility — 40× in this paper
• Accuracy — 35× in this paper · explained in 1 episode
• Benchmark — 35× in this paper · explained in 2 episodes
• Causal Reasoning — 17× in this paper · explained in 2 episodes
• Verifier — 17× in this paper · explained in 2 episodes
• Alignment — 14× in this paper · explained in 1 episode
• Temporal Reasoning — 11× in this paper · explained in 2 episodes
• Benchmarking — 10× in this paper · explained in 3 episodes
• Evaluation Dimensions — 9× in this paper · explained in 3 episodes
• Generative Model — 9× in this paper · explained in 2 episodes
• Agentic Framework — 8× in this paper · explained in 6 episodes
• Generative Models — 7× in this paper · explained in 2 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Reinforcement Learning — 4× in this paper · explained in 4 episodes
• Multimodal Reasoning — 3× in this paper · explained in 5 episodes
• Procedural Knowledge — 3× in this paper · explained in 2 episodes
• Structured Reasoning — 3× in this paper · explained in 3 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic Reasoning — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Agentic Task — 1× in this paper · explained in 1 episode
• Agentic Tasks — 1× in this paper · explained in 1 episode
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Mean Absolute Error — 1× in this paper
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks
• Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
• RS-Gen: A Multi-Stage Agentic Framework for Reasoning and Search-Augmented Image Generation
• HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer
• LLaDA-Image: Building Strong Image Generators with Fully Open Training Recipes
• MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark
• Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget
• Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
• Emerging Properties in Unified Multimodal Pretraining
• SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
• Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?
• GenEval: An Object-Focused Framework for Evaluating Text-to-Image Alignment
• UniREditBench: A Unified Reasoning-based Image Editing Benchmark
• WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models
• Mind-Brush: Integrating Agentic Cognitive Search and Reasoning into Image Generation
• Prompt-to-Prompt Image Editing with Cross Attention Control
• GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
• ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
• SmartEdit: Exploring Complex Instruction-based Image Editing with Multimodal Large Language Models
• MMCTAgent: Multi-modal Critical Thinking Agent Framework for Complex Visual Reasoning

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models