Performs native structural reasoning for proteins, small molecules and inorganic crystals by tokenizing coordinates, topologies and periodic connectivities into a unified structure-aware vocabulary. Treats structural tokens as addressable evidence to produce interpretable prediction traces and improves accuracy across biology, chemistry and materials benchmarks.
Simulates a hospital LIMS to benchmark agentic clinical reasoning: agents inspect demographics, medications, lab orders/results and then submit ICD‑10 diagnostic reports scored by deterministic, context‑aware graders. Ships as an OpenEnv/FastAPI runtime with 8 scenarios, step‑level rewards and trajectory capture for RL, tool‑use and evaluation.
27B multimodal reasoning model built on Qwen3.5-27B that preserves the base model's native multi-token-prediction head, full vision tower, and a 1,048,576-token YaRN context window. Designed for agentic tool use, long-context reasoning, and research deployments; released under Apache-2.0.
50,000 distilled conversational traces (≈120M tokens) generated from GLM-5.2 for high-reasoning text generation and QA, covering STEM, programming, creative and support dialogues; Apache-2.0 licensed.
Provides experimental and in-silico data for 1,440 de novo miniprotein binders designed by Anthropic's Claude models, including per-design kinetics, raw sensorgrams, structure-predictions, and design provenance. Includes two independent wet‑lab assessments and extensive per-design files; data released under CC BY 4.0.
Hugging Face dataset for the MVA Hackathon 2026 containing pediatric rare-disease genomic data (~85 GB across 11 files). Access requires accepting dataset conditions; intended for genomic ML, variant analysis, and hackathon submissions, with notable storage and privacy constraints.
Evaluates AI agents' ability to complete end-to-end scientific workflows by releasing and assessing 97 tasks from a 300-task FrontierChallenge suite across chemistry, materials, life science, and electrochemistry. Finds that top agent configurations achieved only a 20.6% pass rate despite high partial scores, revealing a gap between partial progress/confident completion claims and actual complete scientific deliverables.
Provides a domain-agnostic world-modeling framework that factorizes latent targets into orthogonal predictive components, with dedicated prediction branches and synthesis for multi-domain forecasting and intervention. Demonstrates improved dynamics and long-horizon rollouts across seven domains and includes experimental biological validation.
Turns solved protein structures into FoldingCorpus and Fold2Reason — a post-training recipe that supervises an LLM with discrete structural Q&A plus continuous 3D geometry to improve spatial, graph and scientific reasoning; reports consistent gains across 10 benchmarks.
Shares 211 Claude-designed proteins targeting five scorpion toxins, alongside computational predictions, structures, and lab measurements. Seventeen met the study’s binding criteria, but toxin neutralization has not been tested.
Analyzes DNA in chat, predicting variant effects, identifying sequence features, and continuing sequences. Its hybrid tokenizer represents DNA as 6-mers alongside ordinary text; it is not clinically validated.