Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
A 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-RankingDetecting 11K Classes: Large Scale Object Detection without Fine-Grained Bounding Boxes
Recent advances in deep learning greatly boost the performance of object detection. State-of-the-art methods such as Faster-RCNN, FPN and R-FCN have achieved high accuracy in challenging benchmark datasets. However, thes…
Objectobject-detectionObject DetectionRe-RankingMatching Images and Text with Multi-modal Tensor Fusion and Re-ranking
A major challenge in matching images and text is that they have intrinsically different data distributions and feature representations. Most existing approaches are based either on embedding or classification, the first …
Binary ClassificationGeneral ClassificationImage-text matchingRe-Ranking+2Improving the Results of De novo Peptide Identification via Tandem Mass Spectrometry Using a Genetic Programming-based Scoring Function for Re-ranking Peptide-Spectrum Matches
De novo peptide sequencing algorithms have been widely used in proteomics to analyse tandem mass spectra (MS/MS) and assign them to peptides, but quality-control methods to evaluate the confidence of de novo peptide sequ…
de novo peptide sequencingRe-RankingTMU Transformer System Using BERT for Re-ranking at BEA 2019 Grammatical Error Correction on Restricted Track
We introduce our system that is submitted to the restricted track of the BEA 2019 shared task on grammatical error correction1 (GEC). It is essential to select an appropriate hypothesis sentence from the candidates list …
Grammatical Error CorrectionRe-RankingSentenceNeural and FST-based approaches to grammatical error correction
In this paper, we describe our submission to the BEA 2019 shared task on grammatical error correction. We present a system pipeline that utilises both error detection and correction models. The input text is first correc…
Grammatical Error CorrectionMachine TranslationMulti-Task LearningRe-Ranking+1PANLP at MEDIQA 2019: Pre-trained Language Models, Transfer Learning and Knowledge Distillation
This paper describes the models designated for the MEDIQA 2019 shared tasks by the team PANLP. We take advantages of the recent advances in pre-trained bidirectional transformer language models such as BERT (Devlin et al…
Knowledge DistillationRe-RankingTransfer LearningBaidu Neural Machine Translation Systems for WMT19
In this paper we introduce the systems Baidu submitted for the WMT19 shared task on Chinese{\textless}-{\textgreater}English news translation. Our systems are based on the Transformer architecture with some effective imp…
Data AugmentationDomain AdaptationKnowledge DistillationMachine Translation+2Finding Moments in Video Collections Using Natural Language
We introduce the task of retrieving relevant video moments from a large corpus of untrimmed, unsegmented videos given a natural language query. Our task poses unique challenges as a system must efficiently identify both …
Moment RetrievalRe-RankingRetrievalTemporal Localization+1Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2
This technical report presents an overview of our solution used in the submission to ActivityNet Challenge 2019 Task 1 (\textbf{temporal action proposal generation}) and Task 2 (\textbf{temporal action localization/detec…
Action LocalizationDiversityRe-RankingTask 2+2Careful Selection of Knowledge to solve Open Book Question Answering
Open book question answering is a type of natural language based QA (NLQA) where questions are expected to be answered with respect to a given set of open book facts, and common knowledge about a topic. Recently a challe…
Information RetrievalQuestion AnsweringRe-RankingRetrievalAn Efficient Framework for Visible-Infrared Cross Modality Person Re-Identification
Visible-infrared cross-modality person re-identification (VI-ReId) is an essential task for video surveillance in poorly illuminated or dark environments. Despite many recent studies on person re-identification in the vi…
Cross-Modality Person Re-identificationPerson Re-IdentificationRe-RankingLet's measure run time! Extending the IR replicability infrastructure to include performance aspects
Establishing a docker-based replicability infrastructure offers the community a great opportunity: measuring the run time of information retrieval systems. The time required to present query results to a user is paramoun…
Information RetrievalRe-RankingRetrievalIncorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks
Classical information retrieval (IR) methods, such as query likelihood and BM25, score documents independently w.r.t. each query term, and then accumulate the scores. Assuming query term independence allows precomputing …
Information RetrievalPassage RankingRe-RankingRetrievalSemantic Driven Fielded Entity Retrieval
A common approach for knowledge-base entity search is to consider an entity as a document with multiple fields. Models that focus on matching query terms in different fields are popular choices for searching such entity …
Entity RetrievalRe-RankingRetrievalPentagon at MEDIQA 2019: Multi-task Learning for Filtering and Re-ranking Answers using Language Inference and Question Entailment
Parallel deep learning architectures like fine-tuned BERT and MT-DNN, have quickly become the state of the art, bypassing previous deep and shallow learning methods by a large margin. More recently, pre-trained models fr…
Document ClassificationMulti-Task LearningQuestion AnsweringRe-RankingRe-ranking Based Diversification: A Unifying View
We analyze different re-ranking algorithms for diversification and show that majority of them are based on maximizing submodular/modular functions from the class of parameterized concave/linear over modular functions. We…
DiversityRe-RankingConversational Response Re-ranking Based on Event Causality and Role Factored Tensor Event Embedding
We propose a novel method for selecting coherent and diverse responses for a given dialogue context. The proposed method re-ranks response candidates generated from conversational models by using event causality relation…
Re-RankingAutomatic Acrostic Couplet Generation with Three-Stage Neural Network Pipelines
As one of the quintessence of Chinese traditional culture, couplet compromises two syntactically symmetric clauses equal in length, namely, an antecedent and subsequent clause. Moreover, corresponding characters and phra…
Cultural Vocal Bursts Intensity PredictionRe-RankingLarge-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset
The Google-Landmarks-v2 dataset is the biggest worldwide landmarks dataset characterized by a large magnitude of noisiness and diversity. We present a novel landmark retrieval/recognition system, robust to a noisy and di…
DiversityLandmark RecognitionMetric LearningRe-Ranking+1