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cs.LG2026
Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery
Mingze Li, Yu Rong, Songyou Li +16
Artificial intelligence has accelerated materials discovery through high-throughput prediction and generation, yet the decision problem remains a formidable bottleneck. While curre…
cs.LG2026
DMFlow: Disordered Materials Generation by Flow Matching
Liming Wu, Rui Jiao, Qi Li +4
The design of materials with tailored properties is crucial for technological progress. However, most deep generative models focus exclusively on perfectly ordered crystals, neglec…
cs.LG2025
Geometric Mixture Models for Electrolyte Conductivity Prediction
Anyi Li, Jiacheng Cen, Songyou Li +3
Accurate prediction of ionic conductivity in electrolyte systems is crucial for advancing numerous scientific and technological applications. While significant progress has been ma…