Research team debuts the first deterministic streaming algorithms for non-monotone submodular maximization, delivering superior approximation ratios with minimal memory and real-time throughput on massive datasets.

A research team from the Frontiers Science Center for Flexible Electronics at Northwestern Polytechnical University, jointly with Xi'an Shiyou University and Xidian University, developed a novel crystallization regulation strategy. The team introduced all-inorganic 2D CsPb₂Br₅ nano-flakes as a "heteronucleation agent" for the first time, successfully achieving precise control over the crystallization process of wide-bandgap perovskites.

Developmental dyslexia is characterized by persistent literacy difficulties despite typical intelligence, yet causal links between regional brain activity abnormalities and specific symptoms remain unclear. Kyushu University researchers propose a novel approach in this hypothesis paper, integrating neuroimaging-based subtyping with non-invasive brain stimulation to study dyslexia. Researchers expect this framework to clarify causal brain–behavior relationships and to contribute to personalized educational support and treatment strategies in the future.

 Research team releases the first panoramic LoRA survey, mapping five research fronts—task adaptation, plug-in generalization, speed-ups, federated privacy and real-world deployment—and charting GaaS, continued pre-training and agent roles as next horizons.

Researchers deliver the first comprehensive survey and open NNLCB benchmark of neural universal lossless compressors, taxonomizing 17 state-of-the-art static/adaptive/semi-adaptive algorithms tested across 8.5 GB of multi-source data on CPUs/GPUs.

EduStudio unifies Cognitive Diagnosis and Knowledge Tracing in a modular PyTorch library, cutting new-model code to templated inheritance and offering live leaderboards at edustudio.ai.

ECG-I2S, an open-source Python toolkit, turns smartphone photos of printed ECGs into beat-aligned digital signals and real-time cardiac diagnoses via a one-line pip install.

Researchers present HEGAT, the first interpretable, fine-grained model that jointly predicts document-level event factuality and extracts evidential sentences, achieving SOTA on their refined EB-DEF-v2 corpus.