Ad-Hoc Information Retrieval
28 papers with code • 1 benchmarks • 2 datasets
Ad-hoc information retrieval refers to the task of returning information resources related to a user query formulated in natural language.
Latest papers
Finding the Law: Enhancing Statutory Article Retrieval via Graph Neural Networks
Statutory article retrieval (SAR), the task of retrieving statute law articles relevant to a legal question, is a promising application of legal text processing.
Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval
By making the REM and DAMs disentangled, DDR enables a flexible training paradigm in which REM is trained with supervision once and DAMs are trained with unsupervised data.
Injecting Domain Adaptation with Learning-to-hash for Effective and Efficient Zero-shot Dense Retrieval
In our work, we evaluate LTH and vector compression techniques for improving the downstream zero-shot retrieval accuracy of the TAS-B dense retriever while maintaining efficiency at inference.
Event-Driven Query Expansion
A significant number of event-related queries are issued in Web search.
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.
PARADE: Passage Representation Aggregation for Document Reranking
In this work, we explore strategies for aggregating relevance signals from a document's passages into a final ranking score.
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.
Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-shot Learning
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.
WIKIR: A Python toolkit for building a large-scale Wikipedia-based English Information Retrieval Dataset
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.
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.