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Reranking

Papers

Showing 151–175 of 586 papers

TitleStatusHype
Towards Carbon Footprint-Aware Recommender Systems for Greener Item RecommendationCode0
MAMM-Refine: A Recipe for Improving Faithfulness in Generation with Multi-Agent Collaboration—0
A Multi-Stage Framework with Taxonomy-Guided Reasoning for Occupation Classification Using Large Language Models—0
OSCAR: Online Soft Compression And Reranking—0
MultiConIR: Towards multi-condition Information RetrievalCode0
Advancing Vietnamese Information Retrieval with Learning Objective and Benchmark—0
Evaluating Answer Reranking Strategies in Time-sensitive Question Answering—0
Passage Query Methods for Retrieval and Reranking in Conversational Agents—0
From Retrieval to Generation: Comparing Different Approaches—0
Pragmatic Reasoning improves LLM Code Generation—0
Early-Exit and Instant Confidence Translation Quality EstimationCode0
FaMTEB: Massive Text Embedding Benchmark in Persian Language—0
FineFilter: A Fine-grained Noise Filtering Mechanism for Retrieval-Augmented Large Language Models—0
Gumbel Reranking: Differentiable End-to-End Reranker Optimization—0
E2LVLM:Evidence-Enhanced Large Vision-Language Model for Multimodal Out-of-Context Misinformation Detection—0
NLGR: Utilizing Neighbor Lists for Generative Rerank in Personalized Recommendation Systems—0
Repository-level Code Search with Neural Retrieval MethodsCode0
Hypencoder: Hypernetworks for Information Retrieval—0
RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models—0
Solving the Content Gap in Roblox Game Recommendations: LLM-Based Profile Generation and Reranking—0
Provence: efficient and robust context pruning for retrieval-augmented generation—0
Mitigating GenAI-powered Evidence Pollution for Out-of-Context Multimodal Misinformation Detection—0
ListConRanker: A Contrastive Text Reranker with Listwise Encoding—0
Boosting Text-To-Image Generation via Multilingual Prompting in Large Multimodal ModelsCode0
Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation—0
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