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 ...
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