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20232026
most citedRecJPQ: Training Large-Catalogue Sequential Recommenders

12 citations · 22 across the 7 of their papers we have counts for

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8 papers · 1 filter

cs.IR2026

Predicting Partial Answer Quality and Utility in Agentic Retrieval-Augmented Generation

Fangzheng Tian, Debasis Ganguly, Craig Macdonald

Agentic Retrieval-Augmented Generation (RAG) has become a promising paradigm for multi-hop question answering, where a reasoning model iteratively issues queries to a retriever and…

cs.IR2026

RAQG-QPP: Query Performance Prediction with Retrieved Query Variants and Retrieval Augmented Query Generation

Fangzheng Tian, Debasis Ganguly, Craig Macdonald

Query Performance Prediction (QPP) estimates the retrieval quality of ranking models without the use of any human-assessed relevance judgements, and finds applications in query-spe…

cs.IR2026

Predicting Retrieval Utility and Answer Quality in Retrieval-Augmented Generation

Fangzheng Tian, Debasis Ganguly, Craig Macdonald

The quality of answers generated by large language models (LLMs) in retrieval-augmented generation (RAG) is largely influenced by the contextual information contained in the retrie…

cs.IR2025

Revisiting Query Variants: The Advantage of Retrieval Over Generation of Query Variants for Effective QPP

Fangzheng Tian, Debasis Ganguly, Craig Macdonald

Leveraging query variants (QVs), i.e., queries with potentially similar information needs to the target query, has been shown to improve the effectiveness of query performance pred…

cs.IR2024★ 8 cited

Neural Passage Quality Estimation for Static Pruning

Xuejun Chang, Debabrata Mishra, Craig Macdonald +1

Neural networks -- especially those that use large, pre-trained language models -- have improved search engines in various ways. Most prominently, they can estimate the relevance o…

cs.IR2024★ 1 cited

What Else Would I Like? A User Simulator using Alternatives for Improved Evaluation of Fashion Conversational Recommendation Systems

Maria Vlachou, Craig Macdonald

In Conversational Recommendation Systems (CRS), a user can provide feedback on recommended items at each interaction turn, leading the CRS towards more desirable recommendations. C…

cs.IR2023★ 12 cited

RecJPQ: Training Large-Catalogue Sequential Recommenders

Aleksandr V. Petrov, Craig Macdonald

Sequential Recommendation is a popular recommendation task that uses the order of user-item interaction to model evolving users' interests and sequential patterns in their behaviou…

cs.IR2023★ 1 cited

On Coherence-based Predictors for Dense Query Performance Prediction

Maria Vlachou, Craig Macdonald

Query Performance Prediction (QPP) estimates the effectiveness of a search engine's results in response to a query without relevance judgments. Traditionally, post-retrieval predic…