Search Results - "Craswell, Nick"

Neural information retrieval: introduction to the special issue by Craswell, Nick, Croft, W. Bruce, de Rijke, Maarten, Guo, Jiafeng, Mitra, Bhaskar

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Engineering a multi-purpose test collection for Web retrieval experiments by Bailey, Peter, Craswell, Nick, Hawking, David

“…Past research into text retrieval methods for the Web has been restricted by the lack of a test collection capable of supporting experiments which are both…”
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Towards Group-aware Search Success by Wu, Haolun, Mitra, Bhaskar, Craswell, Nick

“…Traditional measures of search success often overlook the varying information needs of different demographic groups. To address this gap, we introduce a novel…”
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Macaw: An Extensible Conversational Information Seeking Platform by Zamani, Hamed, Craswell, Nick

“…Conversational information seeking (CIS) has been recognized as a major emerging research area in information retrieval. Such research will require data and…”
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Duet at TREC 2019 Deep Learning Track by Mitra, Bhaskar, Craswell, Nick

“…This report discusses three submissions based on the Duet architecture to the Deep Learning track at TREC 2019. For the document retrieval task, we adapt the…”
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UMBRELA: UMbrela is the (Open-Source Reproduction of the) Bing RELevance Assessor by Upadhyay, Shivani, Pradeep, Ronak, Thakur, Nandan, Craswell, Nick, Lin, Jimmy

“…Copious amounts of relevance judgments are necessary for the effective training and accurate evaluation of retrieval systems. Conventionally, these judgments…”
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An Updated Duet Model for Passage Re-ranking by Mitra, Bhaskar, Craswell, Nick

“…We propose several small modifications to Duet---a deep neural ranking model---and evaluate the updated model on the MS MARCO passage ranking task. We report…”
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Measuring search engine quality by HAWKING, David, CRASWELL, Nick, BAILEY, Peter, GRIFFITHS, Kathleen

“…The effectiveness of twenty public search engines is evaluated using TREC-inspired methods and a set of 54 queries taken from real Web search logs. The World…”
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Large language models can accurately predict searcher preferences by Thomas, Paul, Spielman, Seth, Craswell, Nick, Mitra, Bhaskar

“…Relevance labels, which indicate whether a search result is valuable to a searcher, are key to evaluating and optimising search systems. The best way to…”
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Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework by Pradeep, Ronak, Thakur, Nandan, Upadhyay, Shivani, Campos, Daniel, Craswell, Nick, Lin, Jimmy

“…This report provides an initial look at partial results from the TREC 2024 Retrieval-Augmented Generation (RAG) Track. We have identified RAG evaluation as a…”
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SynDL: A Large-Scale Synthetic Test Collection for Passage Retrieval by Rahmani, Hossein A, Wang, Xi, Yilmaz, Emine, Craswell, Nick, Mitra, Bhaskar, Thomas, Paul

“…Large-scale test collections play a crucial role in Information Retrieval (IR) research. However, according to the Cranfield paradigm and the research into…”
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Ragnar\"ok: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track by Pradeep, Ronak, Thakur, Nandan, Sharifymoghaddam, Sahel, Zhang, Eric, Nguyen, Ryan, Campos, Daniel, Craswell, Nick, Lin, Jimmy

“…Did you try out the new Bing Search? Or maybe you fiddled around with Google AI~Overviews? These might sound familiar because the modern-day search stack has…”
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Synthetic Test Collections for Retrieval Evaluation by Rahmani, Hossein A, Craswell, Nick, Yilmaz, Emine, Mitra, Bhaskar, Campos, Daniel

“…Test collections play a vital role in evaluation of information retrieval (IR) systems. Obtaining a diverse set of user queries for test collection…”
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Are We There Yet? A Decision Framework for Replacing Term Based Retrieval with Dense Retrieval Systems by Hofstätter, Sebastian, Craswell, Nick, Mitra, Bhaskar, Zamani, Hamed, Hanbury, Allan

“…Recently, several dense retrieval (DR) models have demonstrated competitive performance to term-based retrieval that are ubiquitous in search systems. In…”
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A Large-Scale Study of Relevance Assessments with Large Language Models: An Initial Look by Upadhyay, Shivani, Pradeep, Ronak, Thakur, Nandan, Campos, Daniel, Craswell, Nick, Soboroff, Ian, Dang, Hoa Trang, Lin, Jimmy

“…The application of large language models to provide relevance assessments presents exciting opportunities to advance information retrieval, natural language…”
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Neural Models for Information Retrieval by Mitra, Bhaskar, Craswell, Nick

“…Neural ranking models for information retrieval (IR) use shallow or deep neural networks to rank search results in response to a query. Traditional learning to…”
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Less is Less: When Are Snippets Insufficient for Human vs Machine Relevance Estimation? by Kazai, Gabriella, Mitra, Bhaskar, Dong, Anlei, Craswell, Nick, Yang, Linjun

“…Traditional information retrieval (IR) ranking models process the full text of documents. Newer models based on Transformers, however, would incur a high…”
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Neural Approaches to Conversational Information Retrieval by Gao, Jianfeng, Xiong, Chenyan, Bennett, Paul, Craswell, Nick

“…A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with…”
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Patterns of gender-specializing query reformulation by Raj, Amifa, Mitra, Bhaskar, Craswell, Nick, Ekstrand, Michael D

“…Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23) [2023] Users of search systems…”
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Intra-Document Cascading: Learning to Select Passages for Neural Document Ranking by Hofstätter, Sebastian, Mitra, Bhaskar, Zamani, Hamed, Craswell, Nick, Hanbury, Allan

“…An emerging recipe for achieving state-of-the-art effectiveness in neural document re-ranking involves utilizing large pre-trained language models - e.g., BERT…”
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