This survey article proposes a clearer view of Natural Language Reasoning (NLR) in the
field of Natural Language Processing (NLP), both conceptually and practically …

Abstract Machine translation is an important and challenging task that aims at automatically
translating natural language sentences from one language into another. Recently …

In the summarization domain, a key requirement for summaries is to be factually consistent
with the input document. Previous work has found that natural language inference (NLI) …

Conducting text retrieval in a dense learned representation space has many intriguing
advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires …

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …

In open question answering (QA), the answer to a question is produced by retrieving and
then analyzing documents that might contain answers to the question. Most open QA …

Pre-trained transformer models, such as BERT and T5, have shown to be highly effective at
ad hoc passage and document ranking. Due to the inherent sequence length limits of these …

When experiencing an information need, users want to engage with a domain expert, but
often turn to an information retrieval system, such as a search engine, instead. Classical …

Fact Verification requires fine-grained natural language inference capability that finds subtle
clues to identify the syntactical and semantically correct but not well-supported claims. This …

In traditional RAG framework, the basic retrieval units are normally short. The common
retrievers like DPR normally work with 100-word Wikipedia paragraphs. Such a design …