Ad-Hoc Information Retrieval
27 papers with code • 1 benchmarks • 1 datasets
Ad-hoc information retrieval refers to the task of returning information resources related to a user query formulated in natural language.
These leaderboards are used to track progress in Ad-Hoc Information Retrieval
Most implemented papers
Text Matching as Image Recognition
An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score.
CEDR: Contextualized Embeddings for Document Ranking
We call this joint approach CEDR (Contextualized Embeddings for Document Ranking).
A Self-Attentive model for Knowledge Tracing
Knowledge tracing is the task of modeling each student's mastery of knowledge concepts (KCs) as (s)he engages with a sequence of learning activities.
PACRR: A Position-Aware Neural IR Model for Relevance Matching
In order to adopt deep learning for information retrieval, models are needed that can capture all relevant information required to assess the relevance of a document to a given user query.
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
This paper provides a unified account of two schools of thinking in information retrieval modelling: the generative retrieval focusing on predicting relevant documents given a query, and the discriminative retrieval focusing on predicting relevancy given a query-document pair.
Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval
Neural IR models, such as DRMM and PACRR, have achieved strong results by successfully capturing relevance matching signals.
A Deep Relevance Matching Model for Ad-hoc Retrieval
Specifically, our model employs a joint deep architecture at the query term level for relevance matching.
Simple Applications of BERT for Ad Hoc Document Retrieval
Following recent successes in applying BERT to question answering, we explore simple applications to ad hoc document retrieval.
Document Ranking with a Pretrained Sequence-to-Sequence Model
We investigate this observation further by varying target words to probe the model's use of latent knowledge.
Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News
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.