Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
FusionANNS: An Efficient CPU/GPU Cooperative Processing Architecture for Billion-scale Approximate Nearest Neighbor Search
Approximate nearest neighbor search (ANNS) has emerged as a crucial component of database and AI infrastructure. Ever-increasing vector datasets pose significant challenges in terms of performance, cost, and accuracy for…
Collaborative FilteringCPUGPURe-RankingEnhancing Scientific Reproducibility Through Automated BioCompute Object Creation Using Retrieval-Augmented Generation from Publications
The exponential growth in computational power and accessibility has transformed the complexity and scale of bioinformatics research, necessitating standardized documentation for transparency, reproducibility, and regulat…
HallucinationLong-Context UnderstandingRAGRe-Ranking+2Inferring Scientific Cross-Document Coreference and Hierarchy with Definition-Augmented Relational Reasoning
We address the fundamental task of inferring cross-document coreference and hierarchy in scientific texts, which has important applications in knowledge graph construction, search, recommendation and discovery. LLMs can …
graph constructionIn-Context LearningRelational ReasoningRe-RankingData Generation via Latent Factor Simulation for Fairness-aware Re-ranking
Synthetic data is a useful resource for algorithmic research. It allows for the evaluation of systems under a range of conditions that might be difficult to achieve in real world settings. In recommender systems, the use…
FairnessRecommendation SystemsRe-RankingMedCodER: A Generative AI Assistant for Medical Coding
Medical coding is essential for standardizing clinical data and communication but is often time-consuming and prone to errors. Traditional Natural Language Processing (NLP) methods struggle with automating coding due to …
Re-RankingVietnamese Legal Information Retrieval in Question-Answering System
In the modern era of rapidly increasing data volumes, accurately retrieving and recommending relevant documents has become crucial in enhancing the reliability of Question Answering (QA) systems. Recently, Retrieval Augm…
HallucinationInformation RetrievalQuestion AnsweringRAG+3rerankers: A Lightweight Python Library to Unify Ranking Methods
This paper presents rerankers, a Python library which provides an easy-to-use interface to the most commonly used re-ranking approaches. Re-ranking is an integral component of many retrieval pipelines; however, there exi…
Re-RankingRetrievalLexBoost: Improving Lexical Document Retrieval with Nearest Neighbors
Sparse retrieval methods like BM25 are based on lexical overlap, focusing on the surface form of the terms that appear in the query and the document. The use of inverted indices in these methods leads to high retrieval e…
Re-RankingRetrievalSEQ+MD: Learning Multi-Task as a SEQuence with Multi-Distribution Data
In e-commerce, the order in which search results are displayed when a customer tries to find relevant listings can significantly impact their shopping experience and search efficiency. Tailored re-ranking system based on…
Multi-Task LearningRe-RankingIt's Not You, It's Me: The Impact of Choice Models and Ranking Strategies on Gender Imbalance in Music Recommendation
As recommender systems are prone to various biases, mitigation approaches are needed to ensure that recommendations are fair to various stakeholders. One particular concern in music recommendation is artist gender fairne…
FairnessMusic RecommendationRecommendation SystemsRe-RankingPlug, Play, and Fuse: Zero-Shot Joint Decoding via Word-Level Re-ranking Across Diverse Vocabularies
Recent advancements in NLP have resulted in models with specialized strengths, such as processing multimodal inputs or excelling in specific domains. However, real-world tasks, like multimodal translation, often require …
Machine TranslationRe-RankingTranslationLeveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards
Recent studies show that large language models (LLMs) struggle with technical standards in telecommunications. We propose a fine-tuned retrieval-augmented generation (RAG) system based on the Phi-2 small language model (…
ChunkingComputational EfficiencyLanguage ModellingQuestion Answering+5Advancing Re-Ranking with Multimodal Fusion and Target-Oriented Auxiliary Tasks in E-Commerce Search
In the rapidly evolving field of e-commerce, the effectiveness of search re-ranking models is crucial for enhancing user experience and driving conversion rates. Despite significant advancements in feature representation…
Re-RankingAMES: Asymmetric and Memory-Efficient Similarity Estimation for Instance-level Retrieval
This work investigates the problem of instance-level image retrieval re-ranking with the constraint of memory efficiency, ultimately aiming to limit memory usage to 1KB per image. Departing from the prevalent focus on pe…
Image RetrievalRe-RankingRetrievalPositive Text Reframing under Multi-strategy Optimization
Differing from sentiment transfer, positive reframing seeks to substitute negative perspectives with positive expressions while preserving the original meaning. With the emergence of pre-trained language models (PLMs), i…
Re-RankingText Generationtext similarityPatchFinder: A Two-Phase Approach to Security Patch Tracing for Disclosed Vulnerabilities in Open-Source Software
Open-source software (OSS) vulnerabilities are increasingly prevalent, emphasizing the importance of security patches. However, in widely used security platforms like NVD, a substantial number of CVE records still lack t…
Re-RankingHidden or Inferred: Fair Learning-To-Rank with Unknown Demographics
As learning-to-rank models are increasingly deployed for decision-making in areas with profound life implications, the FairML community has been developing fair learning-to-rank (LTR) models. These models rely on the ava…
AttributeFairnessLearning-To-RankRe-RankingUniMEL: A Unified Framework for Multimodal Entity Linking with Large Language Models
Multimodal Entity Linking (MEL) is a crucial task that aims at linking ambiguous mentions within multimodal contexts to the referent entities in a multimodal knowledge base, such as Wikipedia. Existing methods focus heav…
Entity Linkingmultimodal interactionRe-RankingEgoCVR: An Egocentric Benchmark for Fine-Grained Composed Video Retrieval
In Composed Video Retrieval, a video and a textual description which modifies the video content are provided as inputs to the model. The aim is to retrieve the relevant video with the modified content from a database of …
Re-RankingRetrievalVideo RetrievalVideo UnderstandingMultimodal Misinformation Detection using Large Vision-Language Models
The increasing proliferation of misinformation and its alarming impact have motivated both industry and academia to develop approaches for misinformation detection and fact checking. Recent advances on large language mod…
Fact CheckingFact VerificationMisinformationRe-Ranking+2