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With the growing success of Large Language models (LLMs) in information-seeking scenarios, search engines are now adopting generative approaches to provide answers along with in-line citations as attribution. While existing work focuses…

Information Retrieval · Computer Science 2024-09-13 Hanane Djeddal , Pierre Erbacher , Raouf Toukal , Laure Soulier , Karen Pinel-Sauvagnat , Sophia Katrenko , Lynda Tamine

The accessibility of documents within a collection holds a pivotal role in Information Retrieval, signifying the ease of locating specific content in a collection of documents. This accessibility can be achieved via two distinct avenues.…

Information Retrieval · Computer Science 2023-11-20 Aman Sinha , Priyanshu Raj Mall , Dwaipayan Roy

Multi-document summarization (MDS) assumes a set of topic-related documents are provided as input. In practice, this document set is not always available; it would need to be retrieved given an information need, i.e. a question or topic…

Computation and Language · Computer Science 2023-10-26 John Giorgi , Luca Soldaini , Bo Wang , Gary Bader , Kyle Lo , Lucy Lu Wang , Arman Cohan

There are many potential benefits to news readers accessing diverse sources. Modern news aggregators do the hard work of organizing the news, offering readers a plethora of source options, but choosing which source to read remains…

Computation and Language · Computer Science 2022-11-10 Philippe Laban , Chien-Sheng Wu , Lidiya Murakhovs'ka , Xiang 'Anthony' Chen , Caiming Xiong

This paper challenges a cross-genre document retrieval task, where the queries are in formal writing and the target documents are in conversational writing. In this task, a query, is a sentence extracted from either a summary or a plot of…

Computation and Language · Computer Science 2017-07-17 Tomasz Jurczyk , Jinho D. Choi

Retrieving keywords (bidwords) with the same intent as query, referred to as close variant keywords, is of prime importance for effective targeted search advertising. For head and torso search queries, sponsored search engines use a huge…

Computation and Language · Computer Science 2021-06-08 Akash Kumar Mohankumar , Nikit Begwani , Amit Singh

This work investigates the effect of gender-stereotypical biases in the content of retrieved results on the relevance judgement of users/annotators. In particular, since relevance in information retrieval (IR) is a multi-dimensional…

Information Retrieval · Computer Science 2022-03-04 Klara Krieg , Emilia Parada-Cabaleiro , Markus Schedl , Navid Rekabsaz

Contextual retrieval is a critical technique for today's search engines in terms of facilitating queries and returning relevant information. This paper reports on the development and evaluation of a system designed to tackle some of the…

Information Retrieval · Computer Science 2014-07-24 Dilip K. Limbu , Andy M. Connor , Russel Pears , Stephen G. MacDonell

Secondary analysis or the reuse of existing survey data is a common practice among social scientists. Searching for relevant datasets in Digital Libraries is a somehow unfamiliar behaviour for this community. Dataset retrieval, especially…

Digital Libraries · Computer Science 2020-10-13 Zeljko Carevic , Dwaipayan Roy , Philipp Mayr

Information Retrieval (IR) is the task of obtaining pieces of data (such as documents or snippets of text) that are relevant to a particular query or need from a large repository of information. While a combination of traditional keyword-…

Information Retrieval · Computer Science 2020-09-07 Samarth Rawal , Chitta Baral

We address the task of sentence retrieval for open-ended dialogues. The goal is to retrieve sentences from a document corpus that contain information useful for generating the next turn in a given dialogue. Prior work on dialogue-based…

Information Retrieval · Computer Science 2022-05-25 Itay Harel , Hagai Taitelbaum , Idan Szpektor , Oren Kurland

Information Retriever (IR) aims to find the relevant documents (e.g. snippets, passages, and articles) to a given query at large scale. IR plays an important role in many tasks such as open domain question answering and dialogue systems,…

Computation and Language · Computer Science 2022-06-01 Man Luo

Domain specific information retrieval process has been a prominent and ongoing research in the field of natural language processing. Many researchers have incorporated different techniques to overcome the technical and domain specificity…

Cross-lingual document classification aims at training a document classifier on resources in one language and transferring it to a different language without any additional resources. Several approaches have been proposed in the literature…

Computation and Language · Computer Science 2018-05-28 Holger Schwenk , Xian Li

In this work, we address multi-modal information needs that contain text questions and images by focusing on passage retrieval for outside-knowledge visual question answering. This task requires access to outside knowledge, which in our…

Information Retrieval · Computer Science 2021-05-11 Chen Qu , Hamed Zamani , Liu Yang , W. Bruce Croft , Erik Learned-Miller

We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for…

Neural document retrieval often treats a corpus as a flat cloud of vectors scored at a single granularity, leaving corpus structure underused and explanations opaque. We use Cobweb--a hierarchy-aware framework--to organize sentence…

Computation and Language · Computer Science 2026-04-17 Anant Gupta , Karthik Singaravadivelan , Zekun Wang

We introduce an approach for open-domain question answering (QA) that retrieves and reads a passage graph, where vertices are passages of text and edges represent relationships that are derived from an external knowledge base or…

Computation and Language · Computer Science 2020-04-14 Sewon Min , Danqi Chen , Luke Zettlemoyer , Hannaneh Hajishirzi

Search engine returns thousands of web pages for a single user query, in which most of them are not relevant. In this context, effective information retrieval from the expanding web is a challenging task, in particular, if the query is…

Information Retrieval · Computer Science 2012-04-09 R. K. Roul , S. K. Sahay

This work compares concept models for cross-language retrieval: First, we adapt probabilistic Latent Semantic Analysis (pLSA) for multilingual documents. Experiments with different weighting schemes show that a weighting method favoring…

Information Retrieval · Computer Science 2014-01-13 Benjamin Roth