For visual generation, discrete autoregressive models often struggle with poor tokenizer reconstruction, difficulties in sampling from large vocabularies, and slow token-by-token generation speeds. We ...

CLAP (Contrastive Language-Assembly Pre-training) is a framework that learns binary code representations through natural language supervision. By aligning binary code with natural language ...