Oblique retrieval, as exemplified by OBLIQ-Bench, asks a retriever to find documents whose relevance is determined by a latent attribute (an implicit stance, an analogous reasoning technique, an authorial fingerprint, or a vague tip-of-the-tongue recollection) that has little or no surface expression in the document. S...
Mahmoud Abdalla, Abdelrahman Abdallah, Shaimaa Sedek et al.· 0 citations
A large-scale empirical study of six zero-cost Query Performance Prediction metrics makes them a practical zero-cost replacement for magnitude thresholding in deployed RAG systems, making them a practical zero-cost replacement for magnitude thresholding in deployed RAG systems.
J. Holdcroft, Abdelrahman Abdallah, Adam Jatowt· 1 citation
This work proposes query-difficulty-gated fusion of reasoning views, a fused ranking that uses no relevance labels at inference, no re-ranking, and no fine-tuning of the retriever; the gate is trained leave-one-task-out.
J. Holdcroft, Abdelrahman Abdallah, Adam Jatowt· 0 citations
Across six collections and three backbones, EXCISE is the strongest system in all eighteen backbone-collection cells against that backbone's own frozen and fine-tuned baselines, and outperforms every fine-tuned cross-encoder, each of which loses no-harm nDCG@10.
Mohammed Ali, Abdelrahman Abdallah, Adam Jatowt· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
