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Ad-hoc information retrieval refers to the task of returning information resources related to a user query formulated in natural language.

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Latest papers with code

Event-Driven Query Expansion

22 Dec 2020guyrosin/event_driven_qe

A significant number of event-related queries are issued in Web search.

AD-HOC INFORMATION RETRIEVAL

1
22 Dec 2020

Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News

EMNLP 2020 nguyenvo09/EMNLP2020

The search can directly warn fake news posters and online users (e. g. the posters' followers) about misinformation, discourage them from spreading fake news, and scale up verified content on social media.

AD-HOC INFORMATION RETRIEVAL FACT CHECKING FACT VERIFICATION FAKE NEWS DETECTION IMAGE SIMILARITY SEARCH MISINFORMATION TEXT MATCHING

27
07 Oct 2020

PARADE: Passage Representation Aggregation for Document Reranking

20 Aug 2020canjiali/PARADE

We present PARADE, an end-to-end Transformer-based model that considers document-level context for document reranking.

AD-HOC INFORMATION RETRIEVAL DOCUMENT-LEVEL KNOWLEDGE DISTILLATION

55
20 Aug 2020

Document Ranking with a Pretrained Sequence-to-Sequence Model

14 Mar 2020castorini/pygaggle

We investigate this observation further by varying target words to probe the model's use of latent knowledge.

CLASSIFICATION DOCUMENT RANKING

84
14 Mar 2020

Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-shot Learning

30 Dec 2019Georgetown-IR-Lab/multilingual-neural-ir

While billions of non-English speaking users rely on search engines every day, the problem of ad-hoc information retrieval is rarely studied for non-English languages.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL ZERO-SHOT LEARNING

1
30 Dec 2019

WIKIR: A Python toolkit for building a large-scale Wikipedia-based English Information Retrieval Dataset

LREC 2020 getalp/wikIR

Since most standard ad-hoc information retrieval datasets publicly available for academic research (e. g. Robust04, ClueWeb09) have at most 250 annotated queries, the recent deep learning models for information retrieval perform poorly on these datasets.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL

25
04 Dec 2019

Deeper Text Understanding for IR with Contextual Neural Language Modeling

22 May 2019AdeDZY/SIGIR19-BERT-IR

Neural networks provide new possibilities to automatically learn complex language patterns and query-document relations.

AD-HOC INFORMATION RETRIEVAL LANGUAGE MODELLING WORD EMBEDDINGS

138
22 May 2019
128
15 Apr 2019

Simple Applications of BERT for Ad Hoc Document Retrieval

26 Mar 2019castorini/birch

Following recent successes in applying BERT to question answering, we explore simple applications to ad hoc document retrieval.

AD-HOC INFORMATION RETRIEVAL QUESTION ANSWERING

115
26 Mar 2019

Joint Optimization of Cascade Ranking Models

WSDM 2019 rmit-ir/joint-cascade-ranking

A cascaded ranking architecture turns ranking into a pipeline of multiple stages, and has been shown to be a powerful approach to balancing efficiency and effectiveness trade-offs in large-scale search systems.

DOCUMENT RANKING INFORMATION RETRIEVAL LEARNING-TO-RANK

7
11 Feb 2019