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