Multi-Modal Asynchronous Reasoning

# Multi-Modal Asynchronous Reasoning ## Project Description This project explores the hypothesis that asynchronous reasoning via rotary embeddings can enhance real-time interaction and reasoning in multi-modal models, improving performance across text, image, and audio data. ## Research Hypothesis Asynchronous reasoning via rotary embeddings can be effectively applied to multi-modal models, enhancing real-time interaction and reasoning across text, image, and audio data. ## Implementation Approach We will develop a multi-modal model incorporating rotary embeddings to enable asynchronous reasoning. The model will be evaluated using standard datasets like VQA and AVQA. ## Setup Instructions 1. Clone the repository: `git clone ` 2. Navigate to the project directory: `cd multi_modal_async_reasoning` 3. Install dependencies: `pip install -r requirements.txt` 4. Download datasets: `bash scripts/download_data.sh` ## Usage Examples - Train the model: `python src/train.py` - Evaluate the model: `python src/evaluate.py` ## Expected Results We expect the model to demonstrate improved interaction speeds and reasoning accuracy compared to traditional multi-modal models. ## References - [Asynchronous Reasoning: Training-Free Interactive Thinking LLMs](http://arxiv.org/abs/2512.10931v1)