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A unified assessment framework reveals hidden insights about agent performance, transforming how we evaluate AI systems.
Integrating 3D structural features with sequence and graph representations in a contrastive learning framework significantly boosts drug-target interaction prediction accuracy.
Radiology report generation models often hide clinically superior reports within their candidate pools, and a simple consensus-based selection method can unlock them.
A new family of GUI agents, GUI-Owl-1.5, leapfrogs existing open-source models on 20+ GUI benchmarks, proving that multi-platform, real-time GUI automation is now within reach.
