Recursion (United States)

DNA-LLM2Vec converts pretrained causal DNA decoders into frozen bidirectional encoders in stages: it opens bidirectional context, repairs the resulting mismatch with masked next-token prediction, then adds contrastive views encoding strand and positional invariance. Across two backbones, DNAGPT and HyenaDNA, and seven biological task families, the benefit is not uniform but depends on task structure and backbone; crop contrastive learning helps most for extended-context families such as enhancer–promoter interaction and Virus-COVID, reaching frozen Avg-EPI MCC of 27.5% and 26.7%.

DNA-LLM2Vec converts pretrained causal DNA decoders into frozen bidirectional encoders in stages: it opens bidirectional context, repairs the resulting mismatch with masked next-token prediction, then adds contrastive views encoding strand and positional invariance. Across two backbones, DNAGPT and HyenaDNA, and seven biological task families, the benefit is not uniform but depends on task structure and backbone; crop contrastive learning helps most for extended-context families such as enhancer–promoter interaction and Virus-COVID, reaching frozen Avg-EPI MCC of 27.5% and 26.7%.