3 papers
cs.IR2026
Do Neural Retrievers Prefer Certain Documents? Evidence of Learned Relevance Priors
Francisco Valentini, Edgar Altszyler, Martin Fajcik
Neural retrievers are trained to estimate query-document relevance from annotated query-document pairs. Yet annotation protocols may not purely reflect relevance: they select only…
cs.IR2025
CLIRudit: Cross-Lingual Information Retrieval of Scientific Documents
Francisco Valentini, Diego Kozlowski, Vincent Larivière
Cross-lingual information retrieval (CLIR) helps users find documents in languages different from their queries. This is especially important in academic search, where key research…
cs.CL2025
MessIRve: A Large-Scale Spanish Information Retrieval Dataset
Francisco Valentini, Viviana Cotik, Damián Furman +3
Information retrieval (IR) is the task of finding relevant documents in response to a user query. Although Spanish is the second most spoken native language, there are few Spanish…