27 citations · 69 across the 20 of their papers we have counts for
12 papers · 1 filter
Controlled Retrieval-augmented Context Evaluation for Long-form RAG
Jia-Huei Ju, Suzan Verberne, Maarten de Rijke +1
Retrieval-augmented generation (RAG) enhances large language models by incorporating context retrieved from external knowledge sources. While the effectiveness of the retrieval mod…
Generative Retrieval with Few-shot Indexing
Arian Askari, Chuan Meng, Mohammad Aliannejadi +3
Existing generative retrieval (GR) methods rely on training-based indexing, which fine-tunes a model to memorise associations between queries and the document identifiers (docids)…
Answer Retrieval in Legal Community Question Answering
Arian Askari, Zihui Yang, Zhaochun Ren +1
The task of answer retrieval in the legal domain aims to help users to seek relevant legal advice from massive amounts of professional responses. Two main challenges hinder applyin…
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…
On the Interpolation of Contextualized Term-based Ranking with BM25 for Query-by-Example Retrieval
Amin Abolghasemi, Arian Askari, Suzan Verberne
Term-based ranking with pre-trained transformer-based language models has recently gained attention as they bring the contextualization power of transformer models into the highly…
LeiBi@COLIEE 2022: Aggregating Tuned Lexical Models with a Cluster-driven BERT-based Model for Case Law Retrieval
Arian Askari, Georgios Peikos, Gabriella Pasi +1
This paper summarizes our approaches submitted to the case law retrieval task in the Competition on Legal Information Extraction/Entailment (COLIEE) 2022. Our methodology consists…
Improving BERT-based Query-by-Document Retrieval with Multi-Task Optimization
Amin Abolghasemi, Suzan Verberne, Leif Azzopardi
Query-by-document (QBD) retrieval is an Information Retrieval task in which a seed document acts as the query and the goal is to retrieve related documents -- it is particular comm…
Expert Finding in Legal Community Question Answering
Arian Askari, Suzan Verberne, Gabriella Pasi
Expert finding has been well-studied in community question answering (QA) systems in various domains. However, none of these studies addresses expert finding in the legal domain, w…
Proceedings of the 17th Dutch-Belgian Information Retrieval Workshop
Alex Brandsen, Anne Dirkson, Wessel Kraaij +4
This volume contains the papers presented at DIR 2018: 17th Dutch-Belgian Information Retrieval Workshop (DIR) held on November 23, 2018 in Leiden. DIR aims to serve as an internat…
Author-topic profiles for academic search
Suzan Verberne, Arjen P. de Vries, Wessel Kraaij
We implemented and evaluated a two-stage retrieval method for personalized academic search in which the initial search results are re-ranked using an author-topic profile. In acade…