Flamingo

Introduction As large language models (LLMs) become increasingly multimodal—capable of reasoning across text, images, audio, and video—a key bottleneck remains: token inefficiency. Particularly in the realm of long video understanding, traditional tokenization methods lead to rapid input length explosion, making processing long videos infeasible without aggressive downsampling or truncation. In this post, we explore the…