Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization
Person re-identification (ReID) aims to extract accurate identity representation features. However, during feature extraction, individual samples are inevitably affected by noise (background, occlusions, and model limita…
Cross-Modal Person Re-IdentificationPerson Re-IdentificationRe-RankingThe RAG Paradox: A Black-Box Attack Exploiting Unintentional Vulnerabilities in Retrieval-Augmented Generation Systems
With the growing adoption of retrieval-augmented generation (RAG) systems, various attack methods have been proposed to degrade their performance. However, most existing approaches rely on unrealistic assumptions in whic…
MisinformationRAGRe-RankingResponse Generation+1Trustworthy Answers, Messier Data: Bridging the Gap in Low-Resource Retrieval-Augmented Generation for Domain Expert Systems
RAG has become a key technique for enhancing LLMs by reducing hallucinations, especially in domain expert systems where LLMs may lack sufficient inherent knowledge. However, developing these systems in low-resource setti…
InformativenessRAGRe-RankingRetrieval+1Improving Transformer Based Line Segment Detection with Matched Predicting and Re-ranking
Classical Transformer-based line segment detection methods have delivered impressive results. However, we observe that some accurately detected line segments are assigned low confidence scores during prediction, causing …
Line Segment DetectionRe-RankingSelaVPR++: Towards Seamless Adaptation of Foundation Models for Efficient Place Recognition
Recent studies show that the visual place recognition (VPR) method using pre-trained visual foundation models can achieve promising performance. In our previous work, we propose a novel method to realize seamless adaptat…
Deep HashingGPURe-RankingRetrieval+1ELIP: Enhanced Visual-Language Foundation Models for Image Retrieval
The objective in this paper is to improve the performance of text-to-image retrieval. To this end, we introduce a new framework that can boost the performance of large-scale pre-trained vision-language models, so that th…
Image RetrievalRe-RankingRetrievalJoint Evaluation of Fairness and Relevance in Recommender Systems with Pareto Frontier
Fairness and relevance are two important aspects of recommender systems (RSs). Typically, they are evaluated either (i) separately by individual measures of fairness and relevance, or (ii) jointly using a single measure …
Exposure FairnessFairnessRecommendation SystemsRe-RankingMulti-Turn Multi-Modal Question Clarification for Enhanced Conversational Understanding
Conversational query clarification enables users to refine their search queries through interactive dialogue, improving search effectiveness. Traditional approaches rely on text-based clarifying questions, which often fa…
Re-RankingRetrievalFineFilter: A Fine-grained Noise Filtering Mechanism for Retrieval-Augmented Large Language Models
Retrieved documents containing noise will hinder Retrieval-Augmented Generation (RAG) from detecting answer clues, necessitating noise filtering mechanisms to enhance accuracy. Existing methods use reranking or summariza…
RAGRerankingRe-RankingRetrieval+1Range and Bird's Eye View Fused Cross-Modal Visual Place Recognition
Image-to-point cloud cross-modal Visual Place Recognition (VPR) is a challenging task where the query is an RGB image, and the database samples are LiDAR point clouds. Compared to single-modal VPR, this approach benefits…
Re-RankingTripletVisual Place RecognitionILIAS: Instance-Level Image retrieval At Scale
This work introduces ILIAS, a new test dataset for Instance-Level Image retrieval At Scale. It is designed to evaluate the ability of current and future foundation models and retrieval techniques to recognize particular …
BenchmarkingImage RetrievalRe-RankingRetrievalQuality-Aware Decoding: Unifying Quality Estimation and Decoding
An emerging research direction in NMT involves the use of Quality Estimation (QE) models, which have demonstrated high correlations with human judgment and can enhance translations through Quality-Aware Decoding. Althoug…
DecoderDocument TranslationNMTRe-Ranking+1Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Retrieval, re-ranking, and retrieval-augmented generation (RAG) are critical components of modern applications in information retrieval, question answering, or knowledge-based text generation. However, existing solutions…
BenchmarkingInformation RetrievalQuestion AnsweringRAG+5ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution
Large Language Models (LLMs) can perform chart question-answering tasks but often generate unverified hallucinated responses. Existing answer attribution methods struggle to ground responses in source charts due to limit…
Chart Question AnsweringQuestion AnsweringRe-RankingRetrieval+1Solving the Content Gap in Roblox Game Recommendations: LLM-Based Profile Generation and Reranking
With the vast and dynamic user-generated content on Roblox, creating effective game recommendations requires a deep understanding of game content. Traditional recommendation models struggle with the inconsistent and spar…
Profile GenerationRecommendation SystemsRerankingRe-RankingMatryoshka Re-Ranker: A Flexible Re-Ranking Architecture With Configurable Depth and Width
Large language models (LLMs) provide powerful foundations to perform fine-grained text re-ranking. However, they are often prohibitive in reality due to constraints on computation bandwidth. In this work, we propose a \t…
Re-RankingASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval
Retrieval-Augmented Generation (RAG) models have drawn considerable attention in modern open-domain question answering. The effectiveness of RAG depends on the quality of the top retrieved documents. However, conventiona…
Language ModelingLanguage ModellingLarge Language ModelOpen-Domain Question Answering+6RAMQA: A Unified Framework for Retrieval-Augmented Multi-Modal Question Answering
Multi-modal retrieval-augmented Question Answering (MRAQA), integrating text and images, has gained significant attention in information retrieval (IR) and natural language processing (NLP). Traditional ranking methods r…
DecoderInformation RetrievalLearning-To-RankMulti-Task Learning+3Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms
Social media platforms utilize Machine Learning (ML) and Artificial Intelligence (AI) powered recommendation algorithms to maximize user engagement, which can result in inadvertent exposure to harmful content. Current mo…
Re-RankingAssisting Mathematical Formalization with A Learning-based Premise Retriever
Premise selection is a crucial yet challenging step in mathematical formalization, especially for users with limited experience. Due to the lack of available formalization projects, existing approaches that leverage lang…
Contrastive LearningRe-RankingRetrieval