Results 61 to 70 of about 498,111 (212)
Aiming at the problems of the incomplete recommendation and sparsity of session data in session recommendation, a new multi-granularity and multi-interest contrast-enhanced hypergraph convolutional network (MGMI-CEHCN) model for session recommendation is
Xingbin Mao, Liang Li, Jiaxing He
doaj +1 more source
Representation of the state’s interests by the prosecutor in economic proceedings
S. V. Dyachenko +1 more
openalex +1 more source
Generative AI voting: fair collective choice is resilient to LLM biases and inconsistencies. [PDF]
Majumdar S, Elkind E, Pournaras E.
europepmc +1 more source
Perception of sex and race diversity in critical care medicine by generative AI: biases, measurement and implications. [PDF]
Chung ME, Choi AE, Sun LY.
europepmc +1 more source
Dual denoising contrastive learning with multi-interest fusion for sequential recommendation. [PDF]
Long H, Lu J, Dai C.
europepmc +1 more source
Representation of different skin colors in German nursing textbooks. [PDF]
Nagata VM, Ohde N, Kottner J.
europepmc +1 more source

