Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
Querying Across Genres for Medical Claims in News
We present a query-based biomedical information retrieval task across two vastly different genres {--} newswire and research literature {--} where the goal is to find the research publication that supports the primary cl…
Biomedical Information RetrievalInformation RetrievalRe-RankingRetrievalUniHD@CL-SciSumm 2020: Citation Extraction as Search
This work presents the entry by the team from Heidelberg University in the CL-SciSumm 2020 shared task at the Scholarly Document Processing workshop at EMNLP 2020. As in its previous iterations, the task is to highlight …
Re-RankingDiDi’s Machine Translation System for WMT2020
This paper describes the DiDi AI Labs’ submission to the WMT2020 news translation shared task. We participate in the translation direction of Chinese->English. In this direction, we use the Transformer as our baseline mo…
Machine TranslationRe-RankingTranslationSamsung R&D Institute Poland submission to WMT20 News Translation Task
This paper describes the submission to the WMT20 shared news translation task by Samsung R&D Institute Poland. We submitted systems for six language directions: English to Czech, Czech to English, English to Polish, Poli…
Re-RankingTranslationIIE’s Neural Machine Translation Systems for WMT20
In this paper we introduce the systems IIE submitted for the WMT20 shared task on German-French news translation. Our systems are based on the Transformer architecture with some effective improvements. Multiscale collabo…
Domain AdaptationKnowledge DistillationMachine TranslationRe-Ranking+1Tilde at WMT 2020: News Task Systems
This paper describes Tilde's submission to the WMT2020 shared task on news translation for both directions of the English-Polish language pair in both the constrained and the unconstrained tracks. We follow our submissio…
Machine TranslationRe-RankingTranslationFlexible retrieval with NMSLIB and FlexNeuART
Our objective is to introduce to the NLP community an existing k-NN search library NMSLIB, a new retrieval toolkit FlexNeuART, as well as their integration capabilities. NMSLIB, while being one the fastest k-NN search li…
Re-RankingRetrievalRECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering
State-of-the-art Machine Reading Comprehension (MRC) models for Open-domain Question Answering (QA) are typically trained for span selection using distantly supervised positive examples and heuristically retrieved negati…
Machine Reading ComprehensionNatural QuestionsOpen-Domain Question AnsweringQuestion Answering+3CoRT: Complementary Rankings from Transformers
Many recent approaches towards neural information retrieval mitigate their computational costs by using a multi-stage ranking pipeline. In the first stage, a number of potentially relevant candidates are retrieved using …
Information RetrievalPassage RetrievalRe-RankingRetrievalDiDi's Machine Translation System for WMT2020
This paper describes DiDi AI Labs' submission to the WMT2020 news translation shared task. We participate in the translation direction of Chinese->English. In this direction, we use the Transformer as our baseline model,…
Machine TranslationRe-RankingTranslationIntegrating Coarse Granularity Part-level Features with Supervised Global-level Features for Person Re-identification
Holistic person re-identification (Re-ID) and partial person re-identification have achieved great progress respectively in recent years. However, scenarios in reality often include both holistic and partial pedestrian i…
Person Re-IdentificationRe-RankingPolice-In-The-Loop Person Re-identification
Person re-identification (Re-ID) has gained significant interest in the computer vision community. One important application of Re-ID is the analysis of CCTV footages for police investigations. This setting poses a chall…
ClusteringPerson Re-IdentificationRe-RankingSLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search
With worldwide concerns surrounding the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there is a rapidly growing body of scientific literature on the virus. Clinicians, researchers, and policy-makers need…
ArticlesRe-RankingImproving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation
Retrieval and ranking models are the backbone of many applications such as web search, open domain QA, or text-based recommender systems. The latency of neural ranking models at query time is largely dependent on the arc…
Knowledge DistillationPassage RankingRecommendation SystemsRe-Ranking+1Multi-Modal Retrieval using Graph Neural Networks
Most real world applications of image retrieval such as Adobe Stock, which is a marketplace for stock photography and illustrations, need a way for users to find images which are both visually (i.e. aesthetically) and co…
Image RetrievalRe-RankingRetrievalLeveraging Semantic and Lexical Matching to Improve the Recall of Document Retrieval Systems: A Hybrid Approach
Search engines often follow a two-phase paradigm where in the first stage (the retrieval stage) an initial set of documents is retrieved and in the second stage (the re-ranking stage) the documents are re-ranked to obtai…
Re-RankingRetrievalImproving Person Re-identification with Iterative Impression Aggregation
Our impression about one person often updates after we see more aspects of him/her and this process keeps iterating given more meetings. We formulate such an intuition into the problem of person re-identification (re-ID)…
Person Re-IdentificationRe-RankingLongformer for MS MARCO Document Re-ranking Task
Two step document ranking, where the initial retrieval is done by a classical information retrieval method, followed by neural re-ranking model, is the new standard. The best performance is achieved by using transformer-…
Document RankingInformation RetrievalRe-RankingRetrievalEnergy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models
The discrepancy between maximum likelihood estimation (MLE) and task measures such as BLEU score has been studied before for autoregressive neural machine translation (NMT) and resulted in alternative training algorithms…
Computational EfficiencyMachine TranslationNMTReranking+3Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning
High false-positive rate is a long-standing challenge for anomaly detection algorithms, especially in high-stake applications. To identify the true anomalies, in practice, analysts or domain experts will be employed to i…
Anomaly DetectionDeep Reinforcement Learningreinforcement-learningReinforcement Learning+2