GitHub - stanford-futuredata/ColBERT: Stanford ColBERT: state-of-the-art neural search (SIGIR'20, TACL'21, NeurIPS'21, NAACL'22, CIKM'22)
MWRC Annual Findings V.01_compressed
Annual findings from the Mouthwash Research Center, covering topics such as artificial intelligence, sustainability, and the intersection of convenience and human behavior.
LinkThis represents a fundamentally different way of thinking about IR systems. Within the index-retrieve-then-rank paradigm, modeling work (e.g., query understanding, document understanding, retrieval, ranking, etc.) is done on top of the index itself. This results in modern IR systems being comprised of a disparate mix of heterogeneous models (e.g., ... See more
Donald Metzler • Rethinking Search: Making Domain Experts out of Dilettantes
GitHub - circlemind-ai/fast-graphrag: RAG that intelligently adapts to your use case, data, and queries
Charles Dickensgithub.com
MMR mitigates retrieval redundancy and mitigates the bias inherent in the document collection. We’ve set the k parameter to 2, which means we will get 2 documents back from retrieval.