作者位次 #7/9SIGIR 2026Oral· Information Retrieval (TOIS)
Explainable, Effective, and Efficient Learning-to-Rank Models Using ILMART
Claudio Lucchese (Ca' · Foscari University of Venice, Venice, Italy) · Franco Maria Nardini · Salvatore Orlando (Ca' · Foscari University of Venice, Venice, Italy) · Raffaele Perego · Alberto Veneri (Ca' · Foscari University of Venice, Venice, Italy) · ISTI-CNR, Pisa, Italy)
摘要
Learning ranking models that are both explainable and effective is an emerging topic within the research area of explainable AI. Several Learning-to-Rank (LtR) algorithms have been recently proposed that build models that are simple to explain and, at the same time, almost as effective as their s...