The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …

Increasingly, users are interacting with information retrieval (IR) systems with the goal of
addressing complex, ill-defined search tasks. As a result, the interest in deconstructing and …

The heterogeneity in recently published knowledge graph embedding models'
implementations, training, and evaluation has made fair and thorough comparisons difficult …

In the context of passive acoustic monitoring (PAM) better models are needed to reliably
gain insights from large amounts of raw, unlabeled data. Bioacoustics foundation models …

We integrate irdatasets, ir_measures, and PyTerrier with TIRA in the Information Retrieval
Experiment Platform (TIREx) to promote more standardized, reproducible, scalable, and …

Hate speech has become a major issue that is currently a hot topic in the domain of social
media. Simultaneously, current proposed methods to address the issue raise concerns …

Deep language models (deep LMs) are increasingly being used for full text retrieval or
within cascade retrieval pipelines as later-stage re-rankers. A problem with using deep LMs …

Evaluation efforts such as TREC, CLEF, NTCIR and FIRE, alongside public leaderboard
such as MS MARCO, are intended to encourage research and track our progress …

The evaluation of recommender systems is an area with unsolved questions at several
levels. Choosing the appropriate evaluation metric is one of such important issues. Ranking …

Recent progress in neural information retrieval has demonstrated large gains in quality,
while often sacrificing efficiency and interpretability compared to classical approaches. We …