Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
Team JL Solution to Google Landmark Recognition 2019
In this paper, we describe our solution to the Google Landmark Recognition 2019 Challenge held on Kaggle. Due to the large number of classes, noisy data, imbalanced class sizes, and the presence of a significant amount o…
Landmark RecognitionRe-RankingRetrievalRankQA: Neural Question Answering with Answer Re-Ranking
The conventional paradigm in neural question answering (QA) for narrative content is limited to a two-stage process: first, relevant text passages are retrieved and, subsequently, a neural network for machine comprehensi…
Question AnsweringReading ComprehensionRe-RankingRetrievalRe-Ranking via Metric Fusion for Object Retrieval and Person Re-Identification
This work studies the unsupervised re-ranking procedure for object retrieval and person re-identification with a specific concentration on an ensemble of multiple metrics (or similarities). While the re-ranking step is i…
3D Shape Classification3D Shape RetrievalImage RetrievalPerson Re-Identification+2Investigating 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-RankingRetrievalPersonalized Ranking in eCommerce Search
We address the problem of personalization in the context of eCommerce search. Specifically, we develop personalization ranking features that use in-session context to augment a generic ranker optimized for conversion and…
Re-RankingSemantic SimilaritySemantic Textual SimilarityFairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search
We present a framework for quantifying and mitigating algorithmic bias in mechanisms designed for ranking individuals, typically used as part of web-scale search and recommendation systems. We first propose complementary…
FairnessRecommendation SystemsRe-RankingDocument 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+1Query Expansion for Cross-Language Question Re-Ranking
Community question-answering (CQA) platforms have become very popular forums for asking and answering questions daily. While these forums are rich repositories of community knowledge, they present challenges for finding …
Community Question AnsweringQuestion AnsweringRe-RankingWord EmbeddingsGeometric Image Correspondence Verification by Dense Pixel Matching
This paper addresses the problem of determining dense pixel correspondences between two images and its application to geometric correspondence verification in image retrieval. The main contribution is a geometric corresp…
Image RetrievalRe-RankingRetrievalVisual LocalizationPersonalized Re-ranking for Recommendation
Ranking is a core task in recommender systems, which aims at providing an ordered list of items to users. Typically, a ranking function is learned from the labeled dataset to optimize the global performance, which produc…
Recommendation SystemsRe-RankingHarvesting Visual Objects from Internet Images via Deep Learning Based Objectness Assessment
The collection of internet images has been growing in an astonishing speed. It is undoubted that these images contain rich visual information that can be useful in many applications, such as visual media creation and dat…
Image GenerationObjectRe-RankingRe-Ranking Words to Improve Interpretability of Automatically Generated Topics
Topics models, such as LDA, are widely used in Natural Language Processing. Making their output interpretable is an important area of research with applications to areas such as the enhancement of exploratory search inte…
Interpretable Machine LearningRe-RankingRetrievalAn 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-RankingUnsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval
We propose an unsupervised hashing method which aims to produce binary codes that preserve the ranking induced by a real-valued representation. Such compact hash codes enable the complete elimination of real-valued featu…
DecoderImage RetrievalRe-RankingRetrievalQuery Term Weighting based on Query Performance Prediction
This work presents a general query term weighting approach based on query performance prediction (QPP). To this end, a given term is weighed according to its predicted effect on query performance. Such an effect is assum…
PredictionRe-RankingRetrievalImproving Semantic Parsing for Task Oriented Dialog
Semantic parsing using hierarchical representations has recently been proposed for task oriented dialog with promising results [Gupta et al 2018]. In this paper, we present three different improvements to the model: cont…
Language ModelingLanguage ModellingRe-RankingSemantic ParsingMachine Reading Comprehension for Answer Re-Ranking in Customer Support Chatbots
Recent advances in deep neural networks, language modeling and language generation have introduced new ideas to the field of conversational agents. As a result, deep neural models such as sequence-to-sequence, Memory Net…
Information RetrievalLanguage ModelingLanguage ModellingMachine Reading Comprehension+4Managing Popularity Bias in Recommender Systems with Personalized Re-ranking
Many recommender systems suffer from popularity bias: popular items are recommended frequently while less popular, niche products, are recommended rarely or not at all. However, recommending the ignored products in the `…
Recommendation SystemsRe-RankingTechnical Report on Visual Quality Assessment for Frame Interpolation
Current benchmarks for optical flow algorithms evaluate the estimation quality by comparing their predicted flow field with the ground truth, and additionally may compare interpolated frames, based on these predictions, …
Optical Flow EstimationRe-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+1