Paper: https://github.com/deepseek-ai/Janus/blob/main/janus_pro_tech_report.pdf Github: https://github.com/deepseek-ai/Janus/tree/main?tab=readme-ov-file The paper introduces Janus-Pro, an improved multimodal model building upon its predecessor, Janus. Janus-Pro boasts enhanced performance in both multimodal understanding and text-to-image generation due to optimized training strategies, expanded datasets (including synthetic aesthetic data), and a larger model size (1B and 7B parameter versions). The architecture uses decoupled visual encoding for improved efficiency and performance across various benchmarks. Results show significant gains over previous state-of-the-art models, although limitations remain in resolution and fine detail. The code and models are publicly available. #ai, #artificialintelligence, #arxiv, #research, #paper, #publication, #llm, #genai, #generativeai, #largevisualmodels, #largelanguagemodels, #largemultimodalmodels, #nlp, #text, #machinelearning, #ml, #nvidia, #openai, #anthropic, #microsoft, #google, #technology, #cuttingedge, #meta, #llama, #chatgpt, #gpt, #elonmusk, #samaltman, #deployment, #engineering, #scholar, #science, #apple, #samsung, #turing, #aiethics, #innovation, #futuretech, #deeplearning, #datascience, #computervision, #autonomoussystems, #robotics, #dataprivacy, #cybersecurity, #digitaltransformation, #quantumcomputing, #aiapplications, #aiethics, #techleadership, #technews, #aiinsights, #aiindustry, #aiadvancements, #futureai, #airesearchers