[PDF] Top 20 Training a Ranking Function for Open Domain Question Answering
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Training a Ranking Function for Open Domain Question Answering
... a question and a document, relevance matching measures the word or phrase level local interactions between pieces of texts in a question and a ...the question and words in the docu- ... See full document
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A Comprehensive Resource to Evaluate Complex Open Domain Question Answering
... needed training and testing instances formed by complex questions and an ordered list of candidate answers from an existing Question Answering system for each of these To this end, we used YourQA ... See full document
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Latent Retrieval for Weakly Supervised Open Domain Question Answering
... trivia question- answer pairs that were scraped from the web (Joshi et ...an open domain QA dataset (Rajpurkar et ...the training data for ...the training data for development, and use ... See full document
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RECIPE: Applying Open Domain Question Answering to Privacy Policies
... the question embedding with the paragraph token embedding using soft attention (Lee et ...for training and 10k for development) based on Wikipedia. Each question in the dataset has an answer which is ... See full document
7
Methods for Using Textual Entailment in Open Domain Question Answering
... original question, all AGQs that do not reach TE are fil- tered from consideration; remaining passages are assigned an entailment confidence score and are sent to the AP module in order to provide an ex- act ... See full document
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Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text
... Open Domain Question Answering (QA) is evolving from complex pipelined systems to end-to-end deep neural ...a question-specific subgraph containing text and KB entities and ...of ... See full document
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Real Time Open Domain Question Answering with Dense Sparse Phrase Index
... Existing open-domain question answering (QA) models are not suitable for real-time us- age because they need to process several long documents on-demand for every input query, which is ... See full document
12
XQA: A Cross lingual Open domain Question Answering Dataset
... Open-domain question answering (OpenQA) aims to answer questions through text retrieval and reading ...of training data (usually in English), which is not available in many other ... See full document
11
Natural Language Generation at Scale: A Case Study for Open Domain Question Answering
... In particular, in our first set of experiments, we investigate the effect of using increasingly larger ontologies with regards to slot types on the perfor- mance of our NLG models for QA. We find that, notwithstanding ... See full document
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HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering
... At the paragraph level, paragraph probability is defined as the degree to which a paragraph can answer the question. This probability is used to measure the quality of a para- graph and targeted to tackle the ... See full document
8
Ranking and Sampling in Open Domain Question Answering
... Open-domain question answering (OpenQA) aims to answer questions based on a num- ber of unlabeled ...a ranking model leveraging the paragraph-question and the paragraph-paragraph ... See full document
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Open domain Factoid Question Answering via Knowledge Graph Search
... a question should be the same as the “expected type” of the property for that ...test question, a set of properties each of which with different probabilities and dif- ferent “expected type”s is ...for ... See full document
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Multi Hop Paragraph Retrieval for Open Domain Question Answering
... each question (above 90% with the top- 32 paragraphs), but fails at retrieving both gold ...a function of the size of the search space of the last retrieval ...SQuAD- Open, the TF-IDF retriever ... See full document
14
Learning Strategies for Open Domain Natural Language Question Answering
... Table 2 compares the performance of different versions of QABLe with those reported by the three systems described above. We wish to discern the particular contribution of transformation rule learning in the QABLe model, ... See full document
6
Domain agnostic Question Answering with Adversarial Training
... Face’s open-source BERT implementation 1 in Py- torch (Paszke et ...For training, we use 6 in-domain datasets, which are SQuAD, TriviaQA (Joshi et ... See full document
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Open Domain Why Question Answering with Adversarial Learning to Encode Answer Texts
... (17,000 question-passage pairs) obtained from 600 million Japanese web pages using the answer- retrieval method of Murata et ...a question-passage pair is composed of a single- sentence question and ... See full document
11
Evolution of Techniques for Question Answering over Knowledge Base: A Survey
... modeling question answering and keyword search tools for Information Retrieval ...[3]–[6]. Question Answering Systems incorporate natural language statements or questions to retrieve ... See full document
6
End to End Open Domain Question Answering with BERTserini
... end-to-end question answering by combin- ing BERT with Anserini, an IR toolkit built on top of the popular open-source Lucene search en- ...end-to-end question an- swering ... See full document
6
Evaluation of baseline information retrieval for Polish open-domain Question Answering system
... of question analysis. First, a question is tagged with WCRFT ...mimic question struc- ...the ranking. In the reported tests all non-stop words from the question were used to form a ... See full document
8
Question Answering in the Biomedical Domain
... QA requires the retrieval of long answers be- fore summarisation or retrieval of answer spans. Punyakanok et al. (2004) introduced the use of a question’s dependency trees and candidate an- swers’ dependency trees and ... See full document
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