Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

Multi-stage ranking pipelines have been a practical solution in modern search systems,
where the first-stage retrieval is to return a subset of candidate documents and latter stages …

Prediction without justification has limited applicability. As a remedy, we learn to extract
pieces of input text as justifications--rationales--that are tailored to be short and coherent, yet …

In this paper, we apply a general deep learning (DL) framework for the answer selection
task, which does not depend on manually defined features or linguistic tools. The basic …

We describe SemEval-2017 Task 3 on Community Question Answering. This year, we reran
the four subtasks from SemEval-2016:(A) Question-Comment Similarity,(B) Question …

Passage-level question answer matching is a challenging task since it requires effective
representations that capture the complex semantic relations between questions and …

As language models are adapted by a more sophisticated and diverse set of users, the
importance of guaranteeing that they provide factually correct information supported by …

Background One of the challenges in large-scale information retrieval (IR) is developing fine-
grained and domain-specific methods to answer natural language questions. Despite the …

This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …

Most text-based information retrieval (IR) systems index objects by words or phrases. These
discrete systems have been augmented by models that use embeddings to measure …