Passage Retrieval

This paper describes the results of some experiments using a new approach to information access that combines techniques from natural language process- ing and knowledge representation with a penalty- based …...

Document Retrieval assumes that a document is independent of its relevance, and non-relevance. Previous works showed that the same assump- tion is being considered for passage retrieval in the context …...

AbstractPassage retrieval is the task of identifying text snippets that are valid answers for a natural language posed question. One way to address this problem is to look at it …...

AbstractOpen-domain question answering relies on efficient passage retrieval to select candidate contexts, where traditional sparse vector space models, such as TF-IDF or BM25, are the de facto method. In this …...

AbstractThis paper presents a highly effective pipeline for passage retrieval in a conversational search setting. The pipeline comprises of two components: Conversational Term Selection (CTS) and Multi-View Reranking (MVR). CTS …...

AbstractIn this work, we introduce back-training, an alternative to self-training for unsupervised domain adaptation (UDA). While self-training generates synthetic training data where natural inputs are aligned with noisy outputs, back-training …...

AbstractPassage retrieval and ranking is a key task in open-domain question answering and information retrieval. Current effective approaches mostly rely on pre-trained deep language model-based retrievers and rankers. These methods …...

AbstractDense retrieval methods have shown great promise over sparse retrieval methods in a range of NLP problems. Among them, dense phrase retrieval—the most fine-grained retrieval unit—is appealing because phrases can …...

AbstractIn various natural language processing tasks, passage retrieval and passage re-ranking are two key procedures in finding and ranking relevant information. Since both the two procedures contribute to the final …...

AbstractA major obstacle to the wide-spread adoption of neural retrieval models is that they require large supervised training sets to surpass traditional term-based techniques, which are constructed from raw corpora. …...

AbstractWe propose a simple and effective re-ranking method for improving passage retrieval in open question answering. The re-ranker re-scores retrieved passages with a zero-shot question generation model, which uses a …...

AbstractSearch-Oriented Conversational AI (SCAI) is an established venue that regularly puts a spotlight upon the recent work advancing the field of conversational search. SCAI’21 was organised as an independent online …...