Asking clarifying questions in open-domain information-seeking conversations
Users often fail to formulate their complex information needs in a single query. As a
consequence, they may need to scan multiple result pages or reformulate their queries …
consequence, they may need to scan multiple result pages or reformulate their queries …
COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization
The COVID-19 global pandemic has resulted in international efforts to understand, track,
and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2 …
and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2 …
Auditing the personalization and composition of politically-related search engine results pages
Search engines are a primary means through which people obtain information in today» s
connected world. Yet, apart from the search engine companies themselves, little is known …
connected world. Yet, apart from the search engine companies themselves, little is known …
Offline evaluation options for recommender systems
We undertake a detailed examination of the steps that make up offline experiments for
recommender system evaluation, including the manner in which the available ratings are …
recommender system evaluation, including the manner in which the available ratings are …
Leveraging llms for unsupervised dense retriever ranking
In this paper we present Large Language Model Assisted Retrieval Model Ranking
(LARMOR), an effective unsupervised approach that leverages LLMs for selecting which …
(LARMOR), an effective unsupervised approach that leverages LLMs for selecting which …
Neural query performance prediction using weak supervision from multiple signals
Predicting the performance of a search engine for a given query is a fundamental and
challenging task in information retrieval. Accurate performance predictors can be used in …
challenging task in information retrieval. Accurate performance predictors can be used in …
Introducing neural bag of whole-words with colberter: Contextualized late interactions using enhanced reduction
Recent progress in neural information retrieval has demonstrated large gains in quality,
while often sacrificing efficiency and interpretability compared to classical approaches. We …
while often sacrificing efficiency and interpretability compared to classical approaches. We …
On the robustness and discriminative power of information retrieval metrics for top-N recommendation
The evaluation of Recommender Systems is still an open issue in the field. Despite its
limitations, offline evaluation usually constitutes the first step in assessing recommendation …
limitations, offline evaluation usually constitutes the first step in assessing recommendation …
The infinite index: Information retrieval on generative text-to-image models
Conditional generative models such as DALL-E and Stable Diffusion generate images
based on a user-defined text, the prompt. Finding and refining prompts that produce a …
based on a user-defined text, the prompt. Finding and refining prompts that produce a …
Assessing ranking metrics in top-N recommendation
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 …
levels. Choosing the appropriate evaluation metric is one of such important issues. Ranking …