Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
A Completely Locale-independent Session-based Recommender System by Leveraging Trained Model
In this paper, we propose a solution that won the 10th prize in the KDD Cup 2023 Challenge Task 2 (Next Product Recommendation for Underrepresented Languages/Locales). Our approach involves two steps: (i) Identify candid…
Product RecommendationRecommendation SystemsRe-RankingTask 2Answer Candidate Type Selection: Text-to-Text Language Model for Closed Book Question Answering Meets Knowledge Graphs
Pre-trained Text-to-Text Language Models (LMs), such as T5 or BART yield promising results in the Knowledge Graph Question Answering (KGQA) task. However, the capacity of the models is limited and the quality decreases f…
Graph Question AnsweringKnowledge GraphsLanguage ModelingLanguage Modelling+2AANet: Aggregation and Alignment Network with Semi-hard Positive Sample Mining for Hierarchical Place Recognition
Visual place recognition (VPR) is one of the research hotspots in robotics, which uses visual information to locate robots. Recently, the hierarchical two-stage VPR methods have become popular in this field due to the tr…
Re-RankingTripletVisual Place RecognitionTPDR: A Novel Two-Step Transformer-based Product and Class Description Match and Retrieval Method
There is a niche of companies responsible for intermediating the purchase of large batches of varied products for other companies, for which the main challenge is to perform product description standardization, i.e., mat…
Contrastive LearningPositionRe-RankingRetrieval+1DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
Recent advances in natural language processing, primarily propelled by Large Language Models (LLMs), have showcased their remarkable capabilities grounded in in-context learning. A promising avenue for guiding LLMs in in…
Dimensionality ReductionIn-Context LearningRe-RankingAutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
Machine-based prediction of real-world events is garnering attention due to its potential for informed decision-making. Whereas traditional forecasting predominantly hinges on structured data like time-series, recent bre…
ArticlesDecision MakingLanguage ModellingMultiple-choice+3Large Language Models Meet Knowledge Graphs to Answer Factoid Questions
Recently, it has been shown that the incorporation of structured knowledge into Large Language Models significantly improves the results for a variety of NLP tasks. In this paper, we propose a method for exploring pre-tr…
Knowledge GraphsRe-RankingHyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models
Advancements in deep neural networks have allowed automatic speech recognition (ASR) systems to attain human parity on several publicly available clean speech datasets. However, even state-of-the-art ASR systems experien…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Language ModellingRe-Ranking+2Fairness for All: Investigating Harms to Within-Group Individuals in Producer Fairness Re-ranking Optimization -- A Reproducibility Study
Recommender systems are widely used to provide personalized recommendations to users. Recent research has shown that recommender systems may be subject to different types of biases, such as popularity bias, leading to an…
AllFairnessRecommendation SystemsRe-RankingDynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking
The core of cross-modal matching is to accurately measure the similarity between different modalities in a unified representation space. However, compared to textual descriptions of a certain perspective, the visual moda…
Image-text matchingRe-RankingRetrievalText Matching+1Provider Fairness and Beyond-Accuracy Trade-offs in Recommender Systems
Recommender systems, while transformative in online user experiences, have raised concerns over potential provider-side fairness issues. These systems may inadvertently favor popular items, thereby marginalizing less pop…
FairnessRecommendation SystemsRe-RankingEvaluating ChatGPT as a Recommender System: A Rigorous Approach
Large Language Models (LLMs) have recently shown impressive abilities in handling various natural language-related tasks. Among different LLMs, current studies have assessed ChatGPT's superior performance across manifold…
Large Language ModelRecommendation SystemsRe-RankingGeo-Encoder: A Chunk-Argument Bi-Encoder Framework for Chinese Geographic Re-Ranking
Chinese geographic re-ranking task aims to find the most relevant addresses among retrieved candidates, which is crucial for location-related services such as navigation maps. Unlike the general sentences, geographic con…
ChunkingMulti-Task LearningRe-RankingLarge Language Models for Generative Recommendation: A Survey and Visionary Discussions
Large language models (LLM) not only have revolutionized the field of natural language processing (NLP) but also have the potential to reshape many other fields, e.g., recommender systems (RS). However, most of the relat…
Recommendation SystemsRe-RankingSurveyA Multi-Perspective Learning to Rank Approach to Support Children's Information Seeking in the Classroom
We introduce a novel re-ranking model that aims to augment the functionality of standard search engines to support classroom search activities for children (ages 6 to 11). This model extends the known listwise learning-t…
Learning-To-RankRe-RankingEnsuring User-side Fairness in Dynamic Recommender Systems
User-side group fairness is crucial for modern recommender systems, aiming to alleviate performance disparities among user groups defined by sensitive attributes like gender, race, or age. In the ever-evolving landscape …
FairnessRecommendation SystemsRe-RankingStationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem
Email platforms need to generate personalized rankings of emails that satisfy user preferences, which may vary over time. We approach this as a recommendation problem based on three criteria: closeness (how relevant the …
Re-RankingBreaking Language Barriers with MMTweets: Advancing Cross-Lingual Debunked Narrative Retrieval for Fact-Checking
Finding previously debunked narratives involves identifying claims that have already undergone fact-checking. The issue intensifies when similar false claims persist in multiple languages, despite the availability of deb…
Fact CheckingMisinformationRe-RankingRetrieval+1Mobile Supply: The Last Piece of Jigsaw of Recommender System
Recommendation system is a fundamental functionality of online platforms. With the development of computing power of mobile phones, some researchers have deployed recommendation algorithms on users' mobile devices to add…
Recommendation SystemsRe-RankingLarge-scale Fully-Unsupervised Re-Identification
Fully-unsupervised Person and Vehicle Re-Identification have received increasing attention due to their broad applicability in surveillance, forensics, event understanding, and smart cities, without requiring any manual …
ClusteringRe-RankingSchedulingVehicle Re-Identification