MIMIC is a split-track encoder-decoder foundation model that unifies sequence reconstruction, prediction, and constrained design across nucleic acids, proteins, and regulatory context using partially observed multimodal inputs.
xtrimopglm: unified 100b-scale pre-trained transformer for deciphering the language of protein
3 Pith papers cite this work. Polarity classification is still indexing.
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SubQuad delivers near-subquadratic retrieval and equity-aware clustering for adaptive immune repertoires, achieving faster throughput and memory use while maintaining recall and subgroup balance on viral and tumor data.
STELLA aligns ESM3 bimodal sequence-structure encodings with Llama-3.1-8B text modeling to claim state-of-the-art results on protein functional description prediction and enzyme-catalyzed reaction prediction.
citing papers explorer
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MIMIC: A Generative Multimodal Foundation Model for Biomolecules
MIMIC is a split-track encoder-decoder foundation model that unifies sequence reconstruction, prediction, and constrained design across nucleic acids, proteins, and regulatory context using partially observed multimodal inputs.
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SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework
SubQuad delivers near-subquadratic retrieval and equity-aware clustering for adaptive immune repertoires, achieving faster throughput and memory use while maintaining recall and subgroup balance on viral and tumor data.
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STELLA: A Multimodal LLM for Protein Functional Annotation via Unified Sequence-Structure Encoding
STELLA aligns ESM3 bimodal sequence-structure encodings with Llama-3.1-8B text modeling to claim state-of-the-art results on protein functional description prediction and enzyme-catalyzed reaction prediction.