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A discrete diffusion model can achieve competitive speech recognition accuracy while transcribing in parallel, breaking the mold of traditional autoregressive methods.
LLMs can nail the JSON schema, but still struggle to extract the right values from images and audio, with accuracy plummeting to 23.7% for audio data.