Yeti is a compact tokenizer for protein structures that delivers strong codebook use, token diversity, and reconstruction while enabling from-scratch multimodal generation of plausible sequences and structures with 10x fewer parameters than ESM3.
Systems and algorithms for convo- lutional multi-hybrid language models at scale
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DNA pretraining suffers from inappropriate evaluation datasets, flawed neighbor-masking, and neglected vocabulary design; the authors supply guidelines and a reproducible testbed to fix them.
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Yeti: A compact protein structure tokenizer for reconstruction and multi-modal generation
Yeti is a compact tokenizer for protein structures that delivers strong codebook use, token diversity, and reconstruction while enabling from-scratch multimodal generation of plausible sequences and structures with 10x fewer parameters than ESM3.
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In Search of Lost DNA Sequence Pretraining
DNA pretraining suffers from inappropriate evaluation datasets, flawed neighbor-masking, and neglected vocabulary design; the authors supply guidelines and a reproducible testbed to fix them.