Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
Improving Black-box Speech Recognition using Semantic Parsing
Speech is a natural channel for human-computer interaction in robotics and consumer applications. Natural language understanding pipelines that start with speech can have trouble recovering from speech recognition errors…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Language ModelingLanguage Modelling+5Cross-Language Question Re-Ranking
We study how to find relevant questions in community forums when the language of the new questions is different from that of the existing questions in the forum. In particular, we explore the Arabic-English language pair…
Machine TranslationRe-RankingWord EmbeddingsMutual Enhancement for Detection of Multiple Logos in Sports Videos
Detecting logo frequency and duration in sports videos provides sponsors an effective way to evaluate their advertising efforts. However, general-purposed object detection methods cannot address all the challenges in spo…
object-detectionObject DetectionRe-RankingRegion-Based Image Retrieval Revisited
Region-based image retrieval (RBIR) technique is revisited. In early attempts at RBIR in the late 90s, researchers found many ways to specify region-based queries and spatial relationships; however, the way to characteri…
AttributeImage RetrievalObjectRe-Ranking+1Exploring and Exploiting Diversity for Image Segmentation
Semantic image segmentation is an important computer vision task that is difficult because it consists of both recognition and segmentation. The task is often cast as a structured output problem on an exponentially large…
DiversityImage SegmentationRe-RankingSegmentation+1Sentence-Level Multilingual Multi-modal Embedding for Natural Language Processing
We propose a novel discriminative ranking model that learns embeddings from multilingual and multi-modal data, meaning that our model can take advantage of images and descriptions in multiple languages to improve embeddi…
Machine TranslationNMTRe-RankingSemantic Textual Similarity+3Divide and Fuse: A Re-ranking Approach for Person Re-identification
As re-ranking is a necessary procedure to boost person re-identification (re-ID) performance on large-scale datasets, the diversity of feature becomes crucial to person reID for its importance both on designing pedestria…
DiversityPerson Re-IdentificationRe-RankingTakeLab-QA at SemEval-2017 Task 3: Classification Experiments for Answer Retrieval in Community QA
In this paper we present the TakeLab-QA entry to SemEval 2017 task 3, which is a question-comment re-ranking problem. We present a classification based approach, including two supervised learning models {--} Support Vect…
Community Question AnsweringGeneral ClassificationInformation RetrievalQuestion Answering+5GW\_QA at SemEval-2017 Task 3: Question Answer Re-ranking on Arabic Fora
This paper describes our submission to SemEval-2017 Task 3 Subtask D, {``}Question Answer Ranking in Arabic Community Question Answering{''}. In this work, we applied a supervised machine learning approach to automatical…
Answer SelectionBIG-bench Machine LearningCommunity Question AnsweringQuestion Answering+1Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking
Deep neural networks have become a primary tool for solving problems in many fields. They are also used for addressing information retrieval problems and show strong performance in several tasks. Training these models re…
Information RetrievalPrivacy PreservingRe-RankingRetrievalClass-Weighted Convolutional Features for Visual Instance Search
Image retrieval in realistic scenarios targets large dynamic datasets of unlabeled images. In these cases, training or fine-tuning a model every time new images are added to the database is neither efficient nor scalable…
image-classificationImage RetrievalInstance SearchRe-Ranking+1Content-Based Weak Supervision for Ad-Hoc Re-Ranking
One challenge with neural ranking is the need for a large amount of manually-labeled relevance judgments for training. In contrast with prior work, we examine the use of weak supervision sources for training that yield p…
Information RetrievalRe-RankingConsistent Translation of Repeated Nouns using Syntactic and Semantic Cues
We propose a method to decide whether two occurrences of the same noun in a source text should be translated consistently, i.e. using the same noun in the target text as well. We train and test classifiers that predict c…
Automatic Post-EditingMachine TranslationRe-RankingTranslationNeural Automatic Post-Editing Using Prior Alignment and Reranking
We present a second-stage machine translation (MT) system based on a neural machine translation (NMT) approach to automatic post-editing (APE) that improves the translation quality provided by a first-stage MT system. Ou…
Automatic Post-EditingMachine TranslationNMTReranking+2Using Images to Improve Machine-Translating E-Commerce Product Listings.
In this paper we study the impact of using images to machine-translate user-generated e-commerce product listings. We study how a multi-modal Neural Machine Translation (NMT) model compares to two text-only approaches: a…
Machine TranslationNMTRe-RankingTranslationDetection of Verbal Multi-Word Expressions via Conditional Random Fields with Syntactic Dependency Features and Semantic Re-Ranking
A description of a system for identifying Verbal Multi-Word Expressions (VMWEs) in running text is presented. The system mainly exploits universal syntactic dependency features through a Conditional Random Fields (CRF) s…
Re-RankingEfficient Large-scale Approximate Nearest Neighbor Search on the GPU
We present a new approach for efficient approximate nearest neighbor (ANN) search in high dimensional spaces, extending the idea of Product Quantization. We propose a two-level product and vector quantization tree that r…
CPUGPUQuantizationRe-RankingMultilingual Multi-modal Embeddings for Natural Language Processing
We propose a novel discriminative model that learns embeddings from multilingual and multi-modal data, meaning that our model can take advantage of images and descriptions in multiple languages to improve embedding quali…
Machine TranslationNMTRe-RankingSemantic Textual Similarity+3Re-ranking Person Re-identification with k-reciprocal Encoding
When considering person re-identification (re-ID) as a retrieval process, re-ranking is a critical step to improve its accuracy. Yet in the re-ID community, limited effort has been devoted to re-ranking, especially those…
Person Re-IdentificationRe-RankingRetrievalA Neural Verb Lexicon Model with Source-side Syntactic Context for String-to-Tree Machine Translation
String-to-tree MT systems translate verbs without lexical or syntactic context on the source side and with limited target-side context. The lack of context is one reason why verb translation recall is as low as 45.5%. We…
Machine TranslationRe-RankingSentenceTranslation