Cross-encoders distilled from large language models (LLMs) are often more effective re-
rankers than cross-encoders fine-tuned on manually labeled data. However, the distilled …

Over the last few years, Quantum Computing (QC) has captured the attention of numerous
researchers pertaining to different fields since, due to technological advancements, QC …

The first International Workshop on Open Web Search (WOWS) was held on Thursday,
March 28th, at ECIR 2024 in Glasgow, UK. The full-day workshop had two calls for …

Only few search engines index the Web at scale. Third parties who want to develop
downstream applications based on web search fully depend on the terms and conditions of …

Cross-encoders are effective passage and document re-rankers but less efficient than other
neural or classic retrieval models. A few previous studies have applied windowed self …

We organize the first international Workshop on Open Web Search (WOWS) at ECIR 2024
with two calls for contributions. The first call targets scientific contributions on cooperative …

Information Retrieval (IR) research is deeply rooted in experimentation and evaluation, and
the Text REtrieval Conference (TREC) has been playing a central role in making that …

Existing cross-encoder re-rankers can be categorized as pointwise, pairwise, or listwise
models. Pair-and listwise models allow passage interactions, which usually makes them …

In real-world Information Retrieval (IR) experiments, the Evaluation Environment (EE) is
exposed to constant change. Documents are added, removed, or updated, and the …

The Information Retrieval (IR) community has a rich history of empirically measuring novel
retrieval methods in terms of effectiveness and efficiency. However, as the search ecosystem …