Vision2Code: A Multi-Domain Benchmark for Evaluating Image-to-Code Generation · DeepSignal
Vision2Code: A Multi-Domain Benchmark for Evaluating Image-to-Code Generation arXiv cs.CV · Ajay Vikram Periasami, Junlin Wang, Bhuwan Dhingra 4d ago · · · · Vision2Code is a benchmark for evaluating multi-domain image-to-code generation without paired reference code.
Key Points Includes 2,169 test examples from 15 datasets. Evaluates models using dataset-specific rubrics. Shows domain-dependent performance across various models. Reader Mode is being prepared.
arXiv cs.CV · Zhuojin Li, Hsin-Pai Cheng, Hong Cai, Shizhong Han, Fatih Porikli 2d ago CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers AI Summary
CoReDiT enhances Diffusion Transformers by optimizing token pruning for efficiency and quality.
📰 Read Original Signal Score
Low signal — niche or repeat coverage.
Weight Score
Source authority 20% 78
Community heat 20% 0
Technical impact 30% 67
📰 Read Original arXiv cs.CV · Alvaro Lopez Pellicer, Plamen Angelov, Marwan Bukhari, Yi Li, Eduardo Soares, Jemma Kerns 2d ago ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows AI Summary
ProtoMedAgent enhances clinical interpretability by integrating multimodal reporting with privacy-aware workflows.
arXiv cs.CV · Kanghyun Baek, Jaihyun Lew, Chaehun Shin, Jungbeom Lee, Sungroh Yoon 2d ago Diagnosing and Correcting Concept Omission in Multimodal Diffusion Transformers AI Summary
The study addresses concept omission in MM-DiTs by introducing Omission Signal Intervention to enhance image generation.
Invisible Orchestrators Suppress Protective Behavior and Dissociate Power-Holders: Safety Risks in Multi-Agent LLM Systems AI Summary
Invisible orchestrators in multi-agent LLM systems pose significant safety risks and affect behavior dynamics.
Enhanced and Efficient Reasoning in Large Learning Models AI Summary
The paper proposes an efficient reasoning method for large language models, enhancing trust in generated content.
arXiv cs.CL · Mokshit Surana, Archit Rathod, Akshaj Satishkumar 2d ago Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study AI Summary
This study evaluates DExperts for mitigating toxicity in LLMs, revealing strengths and weaknesses in safety and latency.
≥75 high · 50–74 medium · <50 low
Why Featured
Vision2Code provides a standardized framework for assessing image-to-code generation, enabling developers, PMs, and investors to gauge advancements and potential in AI-driven software development tools.