test

.cursorrules

@@ -0,0 +1,44 @@
+
+  You are an expert in TypeScript, Node.js, Next.js App Router, React, Shadcn UI, Radix UI and Tailwind.
+
+  Code Style and Structure
+  - Write concise, technical TypeScript code with accurate examples.
+  - Use functional and declarative programming patterns; avoid classes.
+  - Prefer iteration and modularization over code duplication.
+  - Use descriptive variable names with auxiliary verbs (e.g., isLoading, hasError).
+  - Structure files: exported component, subcomponents, helpers, static content, types.
+
+  Naming Conventions
+  - Use lowercase with dashes for directories (e.g., components/auth-wizard).
+  - Favor named exports for components.
+
+  TypeScript Usage
+  - Use TypeScript for all code; prefer interfaces over types.
+  - Avoid enums; use maps instead.
+  - Use functional components with TypeScript interfaces.
+
+  Syntax and Formatting
+  - Use the "function" keyword for pure functions.
+  - Avoid unnecessary curly braces in conditionals; use concise syntax for simple statements.
+  - Use declarative JSX.
+
+  UI and Styling
+  - Use Shadcn UI, Radix, and Tailwind for components and styling.
+  - Implement responsive design with Tailwind CSS; use a mobile-first approach.
+
+  Performance Optimization
+  - Minimize 'use client', 'useEffect', and 'setState'; favor React Server Components (RSC).
+  - Wrap client components in Suspense with fallback.
+  - Use dynamic loading for non-critical components.
+  - Optimize images: use WebP format, include size data, implement lazy loading.
+
+  Key Conventions
+  - Use 'nuqs' for URL search parameter state management.
+  - Optimize Web Vitals (LCP, CLS, FID).
+  - Limit 'use client':
+    - Favor server components and Next.js SSR.
+    - Use only for Web API access in small components.
+    - Avoid for data fetching or state management.
+
+  Follow Next.js docs for Data Fetching, Rendering, and Routing.
+

MLLM_latex/main.tex

@@ -2,7 +2,7 @@
 \usepackage{hyperref}
 
 \title{A Comprehensive Guide to Multimodal Large Language Models in Vision-Language Tasks}
-\author{Contributors}
+\author{MLLM-MARCUS}
 
 \begin{document}