Papers Passage Re-Ranking
“Passage Re-Ranking” 태그가 달린 논문 33편 · 필터 해제
Exploiting Sentence-Level Representations for Passage Ranking
Recently, pre-trained contextual models, such as BERT, have shown to perform well in language related tasks. We revisit the design decisions that govern the applicability of these models for the passage re-ranking task i…
Open-Domain Question AnsweringPassage RankingPassage Re-RankingQuestion Answering+2Text-to-Text Multi-view Learning for Passage Re-ranking
Recently, much progress in natural language processing has been driven by deep contextualized representations pretrained on large corpora. Typically, the fine-tuning on these pretrained models for a specific downstream t…
MULTI-VIEW LEARNINGPassage RankingPassage Re-RankingRe-Ranking+2Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers
Societal biases resonate in the retrieved contents of information retrieval (IR) systems, resulting in reinforcing existing stereotypes. Approaching this issue requires established measures of fairness in respect to the …
DisentanglementFairnessInformation RetrievalModel Selection+4Mitigating the Position Bias of Transformer Models in Passage Re-Ranking
Supervised machine learning models and their evaluation strongly depends on the quality of the underlying dataset. When we search for a relevant piece of information it may appear anywhere in a given passage. However, we…
Passage Re-RankingPositionQuestion AnsweringRe-Ranking+2Improving Passage Re-Ranking with Word N-Gram Aware Coattention Encoder
In text matching applications, coattentions have proved to be highly effective attention mechanisms. Coattention enables the learning to attend based on computing word level affinity scores between two texts. In this pap…
Passage RankingPassage Re-RankingRe-RankingText MatchingMulti-Perspective Semantic Information Retrieval in the Biomedical Domain
Information Retrieval (IR) is the task of obtaining pieces of data (such as documents) that are relevant to a particular query or need from a large repository of information. IR is a valuable component of several downstr…
ArticlesInformation RetrievalLanguage ModellingPassage Re-Ranking+4Learning-to-Rank with BERT in TF-Ranking
This paper describes a machine learning algorithm for document (re)ranking, in which queries and documents are firstly encoded using BERT [1], and on top of that a learning-to-rank (LTR) model constructed with TF-Ranking…
Document RankingLearning-To-RankPassage Re-RankingRe-RankingA Study of BERT for Non-Factoid Question-Answering under Passage Length Constraints
We study the use of BERT for non-factoid question-answering, focusing on the passage re-ranking task under varying passage lengths. To this end, we explore the fine-tuning of BERT in different learning-to-rank setups, co…
Learning-To-RankPassage Re-RankingQuestion AnsweringRe-RankingInvestigating the Successes and Failures of BERT for Passage Re-Ranking
The bidirectional encoder representations from transformers (BERT) model has recently advanced the state-of-the-art in passage re-ranking. In this paper, we analyze the results produced by a fine-tuned BERT model to bett…
Passage Re-RankingRe-RankingRetrievalDocument Expansion by Query Prediction
One technique to improve the retrieval effectiveness of a search engine is to expand documents with terms that are related or representative of the documents' content.From the perspective of a question answering system, …
Passage Re-RankingPredictionQuestion AnsweringRe-Ranking+1An Updated Duet Model for Passage Re-ranking
We propose several small modifications to Duet---a deep neural ranking model---and evaluate the updated model on the MS MARCO passage ranking task. We report significant improvements from the proposed changes based on an…
modelPassage RankingPassage Re-RankingRe-RankingPassage Re-ranking with BERT
Recently, neural models pretrained on a language modeling task, such as ELMo (Peters et al., 2017), OpenAI GPT (Radford et al., 2018), and BERT (Devlin et al., 2018), have achieved impressive results on various natural l…
Language ModelingPassage Re-RankingPassage RetrievalRe-Ranking+1A Study on Passage Re-ranking in Embedding based Unsupervised Semantic Search
State of the art approaches for (embedding based) unsupervised semantic search exploits either compositional similarity (of a query and a passage) or pair-wise word (or term) similarity (from the query and the passage). …
Passage Re-RankingRe-RankingSentenceSentence Embedding+1