26 citations · 83 across the 17 of their papers we have counts for
4 papers · 1 filter
Enhancing Documents with Multidimensional Relevance Statements in Cross-encoder Re-ranking
Rishabh Upadhyay, Arian Askari, Gabriella Pasi +1
In this paper, we propose a novel approach to consider multiple dimensions of relevance beyond topicality in cross-encoder re-ranking. On the one hand, current multidimensional ret…
Generating Synthetic Documents for Cross-Encoder Re-Rankers: A Comparative Study of ChatGPT and Human Experts
Arian Askari, Mohammad Aliannejadi, Evangelos Kanoulas +1
We investigate the usefulness of generative Large Language Models (LLMs) in generating training data for cross-encoder re-rankers in a novel direction: generating synthetic documen…
Retrieval for Extremely Long Queries and Documents with RPRS: a Highly Efficient and Effective Transformer-based Re-Ranker
Arian Askari, Suzan Verberne, Amin Abolghasemi +2
Retrieval with extremely long queries and documents is a well-known and challenging task in information retrieval and is commonly known as Query-by-Document (QBD) retrieval. Specif…
Injecting the BM25 Score as Text Improves BERT-Based Re-rankers
Arian Askari, Amin Abolghasemi, Gabriella Pasi +2
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the relevance score of the lexical model as…