Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
Query-focused Extractive Summarisation for Biomedical and COVID-19 Complex Question Answering
This paper presents Macquarie University's participation to the two most recent BioASQ Synergy Tasks (as per June 2022), and to the BioASQ10 Task~B (BioASQ10b), Phase~B. In these tasks, participating systems are expected…
Question AnsweringRe-RankingRetrievalSentence+1Isotropic Representation Can Improve Dense Retrieval
The recent advancement in language representation modeling has broadly affected the design of dense retrieval models. In particular, many of the high-performing dense retrieval models evaluate representations of query an…
Re-RankingRetrievalRAGUEL: Recourse-Aware Group Unfairness Elimination
While machine learning and ranking-based systems are in widespread use for sensitive decision-making processes (e.g., determining job candidates, assigning credit scores), they are rife with concerns over unintended bias…
AttributecounterfactualDecision MakingFairness+1Towards Confidence-aware Calibrated Recommendation
Recommender systems utilize users' historical data to learn and predict their future interests, providing them with suggestions tailored to their tastes. Calibration ensures that the distribution of recommended item cate…
DiversityRecommendation SystemsRe-RankingScattered or Connected? An Optimized Parameter-efficient Tuning Approach for Information Retrieval
Pre-training and fine-tuning have achieved significant advances in the information retrieval (IR). A typical approach is to fine-tune all the parameters of large-scale pre-trained models (PTMs) on downstream tasks. As th…
Information RetrievalRe-RankingRetrievalReal-time Short Video Recommendation on Mobile Devices
Short video applications have attracted billions of users in recent years, fulfilling their various needs with diverse content. Users usually watch short videos on many topics on mobile devices in a short period of time,…
Recommendation SystemsRe-RankingAdaptive Re-Ranking with a Corpus Graph
Search systems often employ a re-ranking pipeline, wherein documents (or passages) from an initial pool of candidates are assigned new ranking scores. The process enables the use of highly-effective but expensive scoring…
Passage RankingRe-RankingRetrievalBrain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System
With the growth of information on the Web, most users heavily rely on information access systems (e.g., search engines, recommender systems, etc.) in their daily lives. During this procedure, modeling users' satisfaction…
EEGElectroencephalogram (EEG)Recommendation SystemsRe-RankingContent-Based Landmark Retrieval Combining Global and Local Features using Siamese Neural Networks
In this work, we present a method for landmark retrieval that utilizes global and local features. A Siamese network is used for global feature extraction and metric learning, which gives an initial ranking of the landmar…
Metric LearningRe-RankingRetrievalTransfer LearningLarge-Scale Product Retrieval with Weakly Supervised Representation Learning
Large-scale weakly supervised product retrieval is a practically useful yet computationally challenging problem. This paper introduces a novel solution for the eBay Visual Search Challenge (eProduct) held at the Ninth Wo…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONRepresentation LearningRe-Ranking+1Claim-Dissector: An Interpretable Fact-Checking System with Joint Re-ranking and Veracity Prediction
We present Claim-Dissector: a novel latent variable model for fact-checking and analysis, which given a claim and a set of retrieved evidences jointly learns to identify: (i) the relevant evidences to the given claim, (i…
Fact CheckingRe-RankingSentenceUNIMIB at TREC 2021 Clinical Trials Track
This contribution summarizes the participation of the UNIMIB team to the TREC 2021 Clinical Trials Track. We have investigated the effect of different query representations combined with several retrieval models on the r…
Keyword ExtractionRe-RankingRetrievalSparse Pairwise Re-ranking with Pre-trained Transformers
Pairwise re-ranking models predict which of two documents is more relevant to a query and then aggregate a final ranking from such preferences. This is often more effective than pointwise re-ranking models that directly …
Passage RankingRe-RankingRetrievalContrastive Information Transfer for Pre-Ranking Systems
Real-word search and recommender systems usually adopt a multi-stage ranking architecture, including matching, pre-ranking, ranking, and re-ranking. Previous works mainly focus on the ranking stage while very few focus o…
Recommendation SystemsRe-RankingSelection biasThe Role of Complex NLP in Transformers for Text Ranking?
Even though term-based methods such as BM25 provide strong baselines in ranking, under certain conditions they are dominated by large pre-trained masked language models (MLMs) such as BERT. To date, the source of their e…
PositionRe-RankingAccurate Instance-Level CAD Model Retrieval in a Large-Scale Database
We present a new solution to the fine-grained retrieval of clean CAD models from a large-scale database in order to recover detailed object shape geometries for RGBD scans. Unlike previous work simply indexing into a mod…
Re-RankingRetrievalTowards an open-domain chatbot for language practice
State-of-the-art chatbots for English are now able to hold conversations on virtually any topic (e.g. Adiwardana et al., 2020; Roller et al., 2021). However, existing dialogue systems in the language learning domain stil…
ChatbotDialogue GenerationRe-RankingEntity Linking via Explicit Mention-Mention Coreference Modeling
Learning representations of entity mentions is a core component of modern entity linking systems for both candidate generation and making linking predictions. In this paper, we present and empirically analyze a novel tra…
Entity LinkingRe-RankingSImProv: Scalable Image Provenance Framework for Robust Content Attribution
We present SImProv - a scalable image provenance framework to match a query image back to a trusted database of originals and identify possible manipulations on the query. SImProv consists of three stages: a scalable sea…
Re-RankingRetrievalPCDF: A Parallel-Computing Distributed Framework for Sponsored Search Advertising Serving
Traditional online advertising systems for sponsored search follow a cascade paradigm with retrieval, pre-ranking,ranking, respectively. Constrained by strict requirements on online inference efficiency, it tend to be di…
Click-Through Rate PredictionRe-RankingRetrieval