arXiv:2210.15912
Decontamination of the scientific literature
원문 초록
Research misconduct and frauds pollute the scientific literature. Honest errors and malevolent data fabrication, image manipulation, journal hijacking, and plagiarism passed peer review unnoticed. Problematic papers deceive readers, authors citing them, and AI-powered literature-based discovery. Flagship publishers accepted hundreds flawed papers despite claiming to enforce peer review. This application ambitions to decontaminate the scientific literature using curative and preventive actions.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Visual Agentic Reinforcement Fine-Tuning
ForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization
Visual Text Processing: A Comprehensive Review and Unified Evaluation
Step1X-Edit: A Practical Framework for General Image Editing
LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps
Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer
토론
이 논문과 연결된 포럼 글이 아직 없습니다.