Locality-aware news sentiment, ensemble-based property price prediction, and GNN-driven session recommendation are brought within a single real estate recommendation framework that incorporates crime-sensitive and infrastructure-aware locality sentiment to improve recommendation transparency, contextual awareness, and...
Renugadevi Somu, Praveen Kaliavannan, M. Priya· Indian Journal of Science an...· 0 citations
The GATNextHop model is proposed to determine whether a Graph Neural Network, namely the Graph Attention Network, can approximate shortest paths and generalize across topologies and compares the GNN against Dijkstra's algorithm to quantify trade-offs between learned and classical routing approaches.
M-HySMap is presented, a route-aware, activity-weighted multicast hypergraph mapping framework that optimizes distinct destination-core fanout, the union of deterministic mesh routes, and link congestion, and exposes this combinatorial structure in detail, derive a conservative placement lower bound, and describes a po...
ALARM is proposed, a multimodal active–learning framework pairing a frozen large language model (LLM) that encodes course and learner text, a vision transformer (ViT) that “observes” the KG by reading its rendered subgraph image, and a domain–specific acquisition function that selects which labels to query.
A post hoc conformal prediction framework is developed that wraps any trained graph neural network (GNN) surrogate to produce prediction sets with coverage near-nominal levels, and componentwise adaptive (CW-Adaptive) method emerges as the robust universal choice.
Accurate and efficient prediction of chemical nonequilibrium aerodynamic heating remains a fundamental challenge in spacecraft design. High-fidelity computational fluid dynamics (CFD) simulations are computationally prohibitive due to stiff chemical source terms, whereas purely data-driven approaches often lack physica...
Continued efforts in mechanism-driven descriptor design, multi-level modeling, and the integration of computational and experimental data are expected to enable the rational design of next-generation Pt alloys with tailored mechanical properties.
Wen-Ting Lu, Lan-Yu Zhang, Jing Lu et al.· NANO· 0 citations
Analysis of the application methods of artificial intelligence technology in the vehicle routing problem VRP shows that by accurately capturing spatio-temporal features, AI technology will be effective in reducing distribution costs and shortening the time taken to make decisions.
Chen-Yu Lin· Asia Pacific Economic and Ma...· 0 citations
A novel framework that integrates learnable graph convolutions with the geometric multigrid method for solving partial differential equations (PDEs) is presented, effectively transforming the entire multigrid solver into a specialized neural network architecture, rather than combining a classical solver with surrogate...
Blood NfL was associated with both functional and microstructural abnormalities of the salience network and potentially associated with relapse vulnerability in MUD, and higher baseline NfL levels were significantly correlated with greater urine positivity rates during one-year follow-up.
Shyh-Yuh Wei, Yu-Li Liu, Huai-Hsuan Tseng et al.· Psychiatry and Clinical Neur...· 2 citations
C Cerberus, a hybrid detection framework that integrates, in a unique manner, a container-level behavioral analysis running a lightweight one-dimensional convolutional neural network and a collective level of analysis based on behavioral swarm intelligence, demonstrates that it can be applied in practical cloud-native...
Shaymaa Mohammed Abdulameer, Rana M. Hasan, Raghad AbdulHadi AbdulQader et al.· Basrah journal of science· 0 citations
A decision-support pipeline combining disease-specific biomarker correlation graphs, ordinary differential equations (ODEs), deep sequence classification, and retrieval-augmented generation (RAG) is developed, with a decoupling between grounding and diagnostic correctness.
Henri Feto, Abicumaran Uthamacumaran, H. Zenil· 0 citations
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
