Imagine a world where AI can seamlessly read and understand text, regardless of whether it's spoken or written. This is the promise of multi-modal text recognition, a field that seeks to combine the power of automatic speech recognition (ASR) and optical character recognition (OCR) to create truly intelligent systems. However, integrating these different modalities has always been a challenge. Enter Generative Fusion Decoding (GFD), a groundbreaking new framework that's changing the game. Traditional methods often struggle to reconcile the different ways ASR and OCR models process information. GFD overcomes this by cleverly mapping text tokens into a universal byte-level representation. This allows large language models (LLMs) to be integrated directly into the decoding process, acting as a sort of intelligent 'spellchecker' that corrects errors in real-time. The benefits are threefold. First, GFD simplifies the fusion process, eliminating the need for complex retraining and reducing computational latency. Second, it unlocks the full potential of LLMs, allowing them to leverage their vast knowledge to improve the accuracy and robustness of text recognition, especially in challenging scenarios like noisy audio or long, complex documents. Finally, GFD opens doors for exciting new applications. Imagine LLMs boosting Chinese ASR performance by disambiguating homophonous words or effortlessly transcribing long-form audio with remarkable precision. The research demonstrates GFD's effectiveness across various tasks, achieving state-of-the-art results on benchmarks like the NTUML2021 dataset for ASR. While GFD shows immense promise, challenges remain. Researchers have identified areas where the system is susceptible to errors, particularly when dealing with certain types of ASR errors or the nuances of LLM probability estimations. However, these challenges also represent exciting avenues for future research. As GFD evolves, we can expect even more seamless and accurate multi-modal text recognition, paving the way for a future where AI can truly understand the world through both the spoken and written word.