6 papers
Robustness of IR Models to Collection Growth
Emmanouil Georgios Lionis, Debasis Ganguly, Sean MacAvaney
Information Retrieval (IR) systems seek to identify relevant documents within a collection. In practical applications, collections are dynamic, with documents frequently added. We…
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…
Pipeline Inspection, Visualization, and Interoperability in PyTerrier
Emmanouil Georgios Lionis, Craig Macdonald, Sean MacAvaney
PyTerrier provides a declarative framework for building and experimenting with Information Retrieval (IR) pipelines. In this demonstration, we highlight several recent pipeline ope…
To Case or Not to Case: An Empirical Study in Learned Sparse Retrieval
Emmanouil Georgios Lionis, Jia-Huei Ju, Angelos Nalmpantis +3
Learned Sparse Retrieval (LSR) methods construct sparse lexical representations of queries and documents that can be efficiently searched using inverted indexes. Existing LSR appro…
Information Leakage of Sentence Embeddings via Generative Embedding Inversion Attacks
Antonios Tragoudaras, Theofanis Aslanidis, Emmanouil Georgios Lionis +2
Text data are often encoded as dense vectors, known as embeddings, which capture semantic, syntactic, contextual, and domain-specific information. These embeddings, widely adopted…
On the Reproducibility of Learned Sparse Retrieval Adaptations for Long Documents
Emmanouil Georgios Lionis, Jia-Huei Ju
Document retrieval is one of the most challenging tasks in Information Retrieval. It requires handling longer contexts, often resulting in higher query latency and increased comput…