SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two multilingual datasets via joint KGC and alignment loops.

Research team cuts shadow-tomography sample cost to ε^(−3) by seeding FTRL with a rough state guess ϱ, halving measurements when ϱ sits within trace distance Θ(ε) of the true ρ.

PyABV injects high-performance assertion engines into PyRTL, doubling verification coverage on complex HADM designs while sustaining RTL simulation speed for both academia and industry.

MEGI unifies IS, ICE, transposon and phage annotations into the first comprehensive mobile-element dataset, boosting Centroid & SIGI-HMM GI recall by 20% and accuracy by 3%/4% across standard genomes.

 Recent survey delivers the first systematic map of LLM tool-learning, dissecting why tools supercharge models and how four-stage workflows (plan→select→call→respond) perform, while cataloging benchmarks and open challenges to jump-start newcomers.

SharpSMT first fuses DPLL(T) polytope enumeration with new factorization, variable-elimination and caching pre-processing, cutting runtime on instances from program-analysis benchmarks by orders of magnitude.

The rapid spread of animal diseases and pathogen evolution have long posed significant threats to the healthy development of animal husbandry. Traditional nucleic acid detection methods such as PCR rely on expensive equipment and professional personnel, making them difficult to meet the needs of on-site scenarios such as farms and rural areas.