Dense bi-encoders and late-interaction retrievers are usually treated as alternatives, yet they fail on different queries: one vector captures what a text is about, token-level matching finds its exact entities and phrases. Using both today means two models, two indexes and a score-fusion step. We present UIBK-Embeddin...
Abdelrahman Abdallah, Mohammed Ali, Adam Jatowt· 0 citations
Reasoning-intensive retrieval remains difficult for small models. Compact public ColBERTs are usually trained on general-purpose corpora and underperform reasoning-tuned 150M+ baselines on BRIGHT~\cite{bright} by several nDCG@10 points. However, no public reasoning-tuned ColBERT exists at edge scale. We introduce \text...
Abdelrahman Abdallah, Mohammed Ali, Adam Jatowt· 0 citations
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
Results show the rule-based system is consistently strongest on SiLTT and BOUQuET datasets and that TranslateGemma fine-tuned on a curated dataset improves over strong neural baselines but does not surpass the rule-based system in dialectal settings.
Г. Д. Кулик, Miko Pokrywka, Adam Jatowt 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· 2 citations
Experiments across multiple LLM backbones show that SecAwareCoder consistently improves Pass@1 and security robustness over prompting and analyzer-driven baselines, narrowing the security--correctness gap in LLM code generation.
Jie-Xin Wang, Liu-Wen Cao, Xi-Tong Luo et al.· Proceedings of the ACM on So...· 54 citations· ⚡5
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
This tutorial provides a structured and in-depth overview of the complete temporal information access pipeline: Temporal Information Extraction (TIE), Temporal Information Retrieval (TIR), and Temporal Question Answering (TQA).
Bhawna Piryani, Avishek Anand, Omar Alonso et al.· Annual International ACM SIG...· 0 citations
HintEval, an open-source Python library for unified hint generation and evaluation, facilitates systematic research on hint-based question answering (QA) in NLP and IR through human studies in which participants assess generated hints and use them to answer questions.
Jamshid Mozafari, Bhawna Piryani, Abdelrahman Abdallah et al.· 4 citations
A lightweight inference-time correction that estimates and removes a popularity prior from model predictions is proposed, which requires no fine-tuning, is label-free at test time, and adds negligible computational cost.
Abdelrahman Abdallah, Mohammed Ali, Bhawna Piryani et al.· 0 citations
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