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Molt reduces the cognitive load on researchers by offering a clean and compact codebase that maintains high performance, enabling faster iterations in agentic reinforcement learning.
Multimodal models can now achieve state-of-the-art performance in real-world tasks like document understanding and audio-video comprehension with significantly reduced inference latency thanks to novel token-reduction techniques.