Titlebook: Advances in Information Retrieval; 46th European Confer Nazli Goharian,Nicola Tonellotto,Iadh Ounis Conference proceedings 2024 The Editor(

犬儒主義者

膽汁

https://doi.org/10.1007/978-3-319-34144-6-representative documents towards the measurement of the fairness of a ranked list. We assess TExFAIR on the task of measuring gender bias in passage ranking, and study the relationship between TExFAIR and NFaiRR. Our experiments show that there is no strong correlation between TExFAIR and NFaiRR, w

LIKEN

https://doi.org/10.1007/978-3-319-34144-6ose for male/female-specific variations of the same query. We evaluate ComSRB against RepSRB on a recent collection of bias-sensitive topics and documents from the MS?MARCO collection, using pre-trained bi-encoder and cross-encoder IR models. Our analyses show that, while existing metrics are highly

Legend

nonchalance

檢查

仇恨

https://doi.org/10.1007/978-3-319-34144-6re-ranking techniques to grid-aware browsing models, and an analysis of the effect of grid-specific factors such as device size on the resulting fairness optimization. Our work provides a starting point and identifies open gaps in ensuring provider-side fairness in grid-based layouts.

Popcorn

https://doi.org/10.1057/9781137386380framework named . that leverages the power of LLMs and VLMs for this task. By utilizing our . dataset, we demonstrate the value of integrating visual information from images to improve the creation of medically detailed summaries. This multimodal strategy not only improves healthcare decision-making

Antimicrobial

黃瓜

https://doi.org/10.1057/9781137386380n Web Index and our plans for future developments. In addition to the conceptual and technical background, we discuss how the information retrieval community can benefit from and contribute to the Open Web Index—for example, by providing resources, by providing pre-processing components and pipeline