All Competitors

Antibody language model pretrained on 402 million OAS sequences, matching far larger antibody LMs on repertoire tasks at 125M parameters.

Contrastive language-image model for fMRI functional decoding, predicting cognitive tasks, concepts, and domains from brain activation maps.

Generative chemistry foundation model pairing a text-and-SMILES language backbone with a 3D molecular point-cloud encoder for prediction and design.

Sensor-language foundation models aligning wearable biosignals with text for zero-shot activity recognition, retrieval, and sensor captioning.

Generalist medical multimodal LLM for image understanding, visual question answering, and report generation across twelve-plus imaging modalities.

Multimodal ECG model that reads raw 12-lead waveforms and ECG images in one shared space via a structure-aware discrete signal tokenizer.

Multimodal large language model that writes free-form natural-language gene function descriptions directly from a nucleotide sequence and a prompt.

Multimodal clinical foundation model reasoning jointly over 2D and 3D medical images, ECG time-series, and text reports across nine clinical domains.

Instruction-tuned LLM series for multi-property molecule optimization that improves named drug properties while preserving those already in range.

DNA-LLM reasoning model fusing genome foundation model embeddings with an LLM to produce step-by-step pathway and variant effect explanations.

Protein structure retrieval model aligning 3D structures with functional text via contrastive learning, for zero-shot search of PDB and cryo-EM maps.

Reasoning LLM for single-cell type annotation, mapping per-cell expression to labels with marker-by-marker chains of thought on one GPU.

Text-to-protein design retrieving natural protein fragments as a dynamic vocabulary, matching larger baselines on under 0.04% of their training data.

Tri-modal pathology foundation model aligning whole-slide images, transcriptomes, and diagnostic reports, and running on any subset of the three.

Molecular conformation description language encoding 3D geometry as SMILES plus internal-coordinate tokens, turning 3D modeling into a sequence task.

Pathology video-language model that reads histopathology clips and produces a step-by-step histological description plus a sign-out diagnosis.

Retrosynthesis and reaction prediction LLM that jointly learns molecular fragmentation and recombination from a 4.4M-instruction chemistry corpus.

Universal foundation model that jointly generates diagnostic text and segments the corresponding targets across ten biomedical imaging modalities.

Single-cell type annotation pairing a CellMarker-derived knowledge graph with multi-agent LLM retrieval, generalizing across 11 tissue types.

Multi-agent LLM framework for autonomous discovery in protein science, pairing generator and critic agents over design and simulation tools.

Ophthalmic foundation model behind the GlobeReady platform, reading fundus and OCT scans by frozen-encoder retrieval instead of per-site fine-tuning.

Whole-slide multimodal LLM for histopathology, pairing a frozen pathology encoder with a LoRA-tuned LLaMA2-7B for pan-cancer diagnostic Q&A.

Single-cell foundation model reading scRNA-seq profiles as ranked gene-name sentences, scaled on Gemma-2 for annotation, reasoning and drug screens.