6 citations · 6 across the 3 of their papers we have counts for
4 papers
Optimal Re-Ranking Depth
Siqing Huo, Andrew Parry, Debasis Ganguly +1
Second-stage neural rankers are commonly applied with a fixed re-ranking depth, assuming that retrieval effectiveness saturates as depth increases. Prior research has questioned th…
A Sequential Decision Framework for Evaluating LLM-Guided Search
Siqing Huo, Andrew Parry, Debasis Ganguly +2
Recent systems applying retrieval-augmented generation (RAG) and "deep research" iteratively generate queries, retrieve documents, and examine their contents, using the resulting i…
Towards a Relevance Posterior in Neural Information Access
Andrew Parry, Emmanouil Georgios Lionis, Debasis Ganguly +1
Modern information retrieval systems typically operationalise relevance as a query-conditional score computed at inference time. This design choice has become dominant such that al…
Constructing and Evaluating Declarative RAG Pipelines in PyTerrier
Craig Macdonald, Jinyuan Fang, Andrew Parry +1
Search engines often follow a pipeline architecture, where complex but effective reranking components are used to refine the results of an initial retrieval. Retrieval augmented ge…