A-CODE presents a fully atomic one-stage multimodal diffusion model for protein co-design that claims superior unconditional generation performance over prior one- and two-stage models plus a tenfold success-rate gain on hard binder-design tasks.
Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, 630(8016):493–500
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Frontier LLMs reason well about past science but are near chance at judging whether specific advances will happen, systematically late on when, and overconfident — even with extra pre-cutoff knowledge.
Non-iterative amino-acid-level quantum sampling on IBM Heron R2 predicts 5–18-residue pocket peptides with 27–71% better RMSD than AI and VQE baselines while reconstructing approximate energy landscapes.
Crys-JEPA introduces a joint embedding predictive architecture that creates an energy-aware latent space, enabling embedding-based stability screening and a refinement pipeline that yields up to 72.7% gains on the V.S.U.N. metric for crystal generation.
CryoSampler fine-tunes Boltz-2 directly on cryo-EM maps to predict atomic conformational ensembles with higher accuracy than prior methods and shows early signs of generalizing to unseen sequences in the same protein family.
SymDrift makes drifting models produce symmetry-invariant samples in one step via symmetrized coordinate drifts or G-invariant embeddings, outperforming prior one-shot baselines on molecular benchmarks and cutting compute by up to 40x.
RIDER improves RNA 3D structural similarity by over 100% using RL-guided diffusion and discovers non-native sequence designs.
DAO pretrains Siamese diffusion-based models on stable/unstable crystal data to achieve 100% experimental match on Cr6Os2 and 2000x speedup over DFT on real superconductors.
TriProRep pretrains on three aligned protein views and improves results on homodimer co-folding and related structure tasks in the new RepSP benchmark.
VQ-VAE concept learning enables controllable recombination of crystal motifs to generate structures with reported gains in validity-stability-uniqueness-novelty metrics on MP-20 and Alex-MP-20.
MicroWorld constructs a multimodal attributed property graph from scientific image-caption data and augments MLLM prompts via retrieval to raise Qwen3-VL-8B performance by 37.5% on MicroVQA and 6% on MicroBench.
citing papers explorer
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A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion
A-CODE presents a fully atomic one-stage multimodal diffusion model for protein co-design that claims superior unconditional generation performance over prior one- and two-stage models plus a tenfold success-rate gain on hard binder-design tasks.
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Scientific reasoning does not reliably translate into scientific forecasting in frontier AI
Frontier LLMs reason well about past science but are near chance at judging whether specific advances will happen, systematically late on when, and overconfident — even with extra pre-cutoff knowledge.
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Quantum Sampling Architecture for Protein Structure Reconstruction on Utility-Scale Hardware
Non-iterative amino-acid-level quantum sampling on IBM Heron R2 predicts 5–18-residue pocket peptides with 27–71% better RMSD than AI and VQE baselines while reconstructing approximate energy landscapes.
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Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement
Crys-JEPA introduces a joint embedding predictive architecture that creates an energy-aware latent space, enabling embedding-based stability screening and a refinement pipeline that yields up to 72.7% gains on the V.S.U.N. metric for crystal generation.
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Modeling Atomic Conformational Ensembles of Proteins via Test-Time Supervision of Boltz-2 on Cryo-EM Density Maps
CryoSampler fine-tunes Boltz-2 directly on cryo-EM maps to predict atomic conformational ensembles with higher accuracy than prior methods and shows early signs of generalizing to unseen sequences in the same protein family.
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SymDrift: One-Shot Generative Modeling under Symmetries
SymDrift makes drifting models produce symmetry-invariant samples in one step via symmetrized coordinate drifts or G-invariant embeddings, outperforming prior one-shot baselines on molecular benchmarks and cutting compute by up to 40x.
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RIDER: 3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion
RIDER improves RNA 3D structural similarity by over 100% using RL-guided diffusion and discovers non-native sequence designs.
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Siamese Foundation Models for Crystal Structure Prediction
DAO pretrains Siamese diffusion-based models on stable/unstable crystal data to achieve 100% experimental match on Cr6Os2 and 2000x speedup over DFT on real superconductors.
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Atom-level Protein Representation Learning Improves Protein Structure Prediction
TriProRep pretrains on three aligned protein views and improves results on homodimer co-folding and related structure tasks in the new RepSP benchmark.
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Composable Crystals: Controllable Materials Discovery via Concept Learning
VQ-VAE concept learning enables controllable recombination of crystal motifs to generate structures with reported gains in validity-stability-uniqueness-novelty metrics on MP-20 and Alex-MP-20.
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MicroWorld: Empowering Multimodal Large Language Models to Bridge the Microscopic Domain Gap with Multimodal Attribute Graph
MicroWorld constructs a multimodal attributed property graph from scientific image-caption data and augments MLLM prompts via retrieval to raise Qwen3-VL-8B performance by 37.5% on MicroVQA and 6% on MicroBench.