P-01
Towards Autonomous Mechanistic Reasoning in Virtual Cells
P-02
DNACHUNKER: Learnable Tokenization for DNA Language Models
P-03
Riemannian MeanFlow
P-04
Learning Adaptive Perturbation-Conditioned Contexts for Robust Transcriptional Response Prediction
P-05
CatFlow: Co-generation of Slab-Adsorbate Systems via Flow Matching
P-06
Machine Learning Hamiltonians are Accurate Energy-Force Predictors
P-07
INDIBATOR: Diverse and Fact-Grounded Individuality for Multi-Agent Debate in Molecular Discovery
P-08
Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
P-09
How Do Co-folding Models Organize Structural Information?
P-10
A Structured LLM Framework for Inorganic Material Synthesis Planning
P-11
Density of States-Intermediated Crystal Generation for Material Inverse Design
P-12
Retro-Forge: A Multi-Step Pairwise Retrosynthesis Framework for Solid-State Materials Synthesis
P-13
EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D Partial Differential Equations
P-14
COMPASS: Decoupled Latent Steering for Protein Conformational Transitions
P-15
Position: Significant impact of numerical precision in scientific machine learning
P-16
Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors
P-17
HEXST: Hexagonal Shifted-Window Transformer for Spatial Transcriptomics Gene Expression Prediction
P-18
Natural-Language-Guided Generator-Agnostic Shortlisting for Protein Binder Design
P-19
ProMiSE: Protein Multi-state Structure Evaluation Benchmark in Biological Contexts
P-20
Routing by Reaching: Composition of Pre-trained GFlowNets for Multi-Objective Generation
