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Reranking

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Showing 2650 of 586 papers

TitleStatusHype
Global Features are All You Need for Image Retrieval and RerankingCode2
Easy-to-Hard Generalization: Scalable Alignment Beyond Human SupervisionCode2
LamRA: Large Multimodal Model as Your Advanced Retrieval AssistantCode2
CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and RerankingCode2
LitSearch: A Retrieval Benchmark for Scientific Literature SearchCode2
Improving Bilingual Lexicon Induction with Cross-Encoder RerankingCode1
2nd Place Solution to Google Landmark Retrieval 2021Code1
Enhancing Mobile "How-to" Queries with Automated Search Results Verification and RerankingCode1
HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer RerankingCode1
Efficient k-NN Search with Cross-Encoders using Adaptive Multi-Round CUR DecompositionCode1
HypR: A comprehensive study for ASR hypothesis revising with a reference corpusCode1
AcuRank: Uncertainty-Aware Adaptive Computation for Listwise RerankingCode1
Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic FidelityCode1
Generative Flow Network for Listwise RecommendationCode1
AutoBencher: Creating Salient, Novel, Difficult Datasets for Language ModelsCode1
Generating Scientific Definitions with Controllable ComplexityCode1
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward HackingCode1
Instance-level Image Retrieval using Reranking TransformersCode1
Article Reranking by Memory-Enhanced Key Sentence Matching for Detecting Previously Fact-Checked ClaimsCode1
Fast and Accurate Deep Bidirectional Language Representations for Unsupervised LearningCode1
Fine-Grained Fashion Similarity Learning by Attribute-Specific Embedding NetworkCode1
Expand, Rerank, and Retrieve: Query Reranking for Open-Domain Question AnsweringCode1
Enhancing High-order Interaction Awareness in LLM-based Recommender ModelCode1
2nd Place and 2nd Place Solution to Kaggle Landmark Recognition andRetrieval Competition 2019Code1
Explaining Patterns in Data with Language Models via Interpretable AutopromptingCode1
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