{"total":83,"rows":[{"id":"2402.03216","title":"M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation","created":"2024-02-05","cited_by_count":1073,"area":"distill"},{"id":"2402.19473","title":"Retrieval-Augmented Generation for AI-Generated Content: A Survey","created":"2024-02-29","cited_by_count":354,"area":"rag"},{"id":"2209.11755","title":"Promptagator: Few-shot Dense Retrieval From 8 Examples","created":"2022-09-23","cited_by_count":235,"area":null},{"id":"2303.07678","title":"Query2doc: Query Expansion with Large Language Models","created":"2023-03-14","cited_by_count":149,"area":null},{"id":"2205.12035","title":"RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder","created":"2022-05-24","cited_by_count":118,"area":null},{"id":"2205.04733","title":"From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective","created":"2022-05-10","cited_by_count":98,"area":null},{"id":"2311.07838","title":"LLatrieval: LLM-Verified Retrieval for Verifiable Generation","created":"2023-11-14","cited_by_count":52,"area":null},{"id":"2206.10128","title":"Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation","created":"2022-06-21","cited_by_count":48,"area":null},{"id":"2206.10658","title":"Questions Are All You Need to Train a Dense Passage Retriever","created":"2022-06-21","cited_by_count":47,"area":null},{"id":"2203.08372","title":"Multi-View Document Representation Learning for Open-Domain Dense Retrieval","created":"2022-03-16","cited_by_count":41,"area":null},{"id":"2205.09153","title":"ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrieval","created":"2022-05-18","cited_by_count":41,"area":null},{"id":"2206.08063","title":"Towards Robust Ranker for Text Retrieval","created":"2022-06-16","cited_by_count":37,"area":null},{"id":"2504.08748","title":"A Survey of Multimodal Retrieval-Augmented Generation","created":"2025-03-26","cited_by_count":37,"area":"rag"},{"id":"2212.10423","title":"Fine-Grained Distillation for Long Document Retrieval","created":"2022-12-20","cited_by_count":29,"area":"distill"},{"id":"2402.17497","title":"REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering","created":"2024-02-27","cited_by_count":28,"area":"rag"},{"id":"2203.03367","title":"Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrieval","created":"2022-03-07","cited_by_count":27,"area":null},{"id":"2307.04642","title":"TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction","created":"2023-07-07","cited_by_count":25,"area":"rag"},{"id":"2406.17605","title":"NativE: Multi-modal Knowledge Graph Completion in the Wild","created":"2024-03-28","cited_by_count":23,"area":null},{"id":"2201.10866","title":"CodeRetriever: Unimodal and Bimodal Contrastive Learning for Code Search","created":"2022-01-26","cited_by_count":21,"area":null},{"id":"2209.13335","title":"PROD: Progressive Distillation for Dense Retrieval","created":"2022-09-27","cited_by_count":21,"area":null},{"id":"2210.11773","title":"SimANS: Simple Ambiguous Negatives Sampling for Dense Text Retrieval","created":"2022-10-21","cited_by_count":21,"area":null},{"id":"2205.10569","title":"HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer Reranking","created":"2022-05-21","cited_by_count":20,"area":null},{"id":"2205.11194","title":"UnifieR: A Unified Retriever for Large-Scale Retrieval","created":"2022-05-23","cited_by_count":19,"area":null},{"id":"2204.00185","title":"Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings","created":"2022-04-01","cited_by_count":17,"area":"distill"},{"id":"2208.07670","title":"ConTextual Masked Auto-Encoder for Dense Passage Retrieval","created":"2022-08-16","cited_by_count":16,"area":null},{"id":"2208.13661","title":"LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval","created":"2022-08-29","cited_by_count":15,"area":null},{"id":"2407.06992","title":"Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspective","created":"2024-07-09","cited_by_count":15,"area":null},{"id":"2305.02564","title":"RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models","created":"2023-05-04","cited_by_count":13,"area":null},{"id":"2211.01267","title":"Multi-Vector Retrieval as Sparse Alignment","created":"2022-11-02","cited_by_count":12,"area":null},{"id":"2205.08794","title":"LogiGAN: Learning Logical Reasoning via Adversarial Pre-training","created":"2022-05-18","cited_by_count":11,"area":"lr"},{"id":"2301.12005","title":"EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval","created":"2023-01-27","cited_by_count":11,"area":"distill"},{"id":"2401.10487","title":"Generative Dense Retrieval: Memory Can Be a Burden","created":"2024-01-19","cited_by_count":11,"area":null},{"id":"2504.17884","title":"Unsupervised Corpus Poisoning Attacks in Continuous Space for Dense Retrieval","created":"2025-04-24","cited_by_count":11,"area":null},{"id":"2112.07771","title":"Boosted Dense Retriever","created":"2021-12-14","cited_by_count":10,"area":null},{"id":"2402.13542","title":"ARL2: Aligning Retrievers for Black-box Large Language Models via Self-guided Adaptive Relevance Labeling","created":"2024-02-21","cited_by_count":10,"area":"rag"},{"id":"2203.05465","title":"LoopITR: Combining Dual and Cross Encoder Architectures for Image-Text Retrieval","created":"2022-03-10","cited_by_count":9,"area":null},{"id":"2212.09598","title":"Query-as-context Pre-training for Dense Passage Retrieval","created":"2022-12-19","cited_by_count":9,"area":null},{"id":"2406.17262","title":"D2LLM: Decomposed and Distilled Large Language Models for Semantic Search","created":"2024-06-25","cited_by_count":9,"area":"distill"},{"id":"2210.11708","title":"Metric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning","created":"2022-10-21","cited_by_count":8,"area":"lr"},{"id":"2212.07249","title":"APOLLO: An Optimized Training Approach for Long-form Numerical Reasoning","created":"2022-12-14","cited_by_count":8,"area":null},{"id":"2210.09597","title":"Soft-Labeled Contrastive Pre-training for Function-level Code Representation","created":"2022-10-18","cited_by_count":7,"area":null},{"id":"2212.07841","title":"MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders are Better Dense Retrievers","created":"2022-12-15","cited_by_count":7,"area":null},{"id":"2311.02834","title":"CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval","created":"2023-11-06","cited_by_count":6,"area":"moe"},{"id":"2411.12235","title":"BoolQuestions: Does Dense Retrieval Understand Boolean Logic in Language?","created":"2024-11-19","cited_by_count":6,"area":null},{"id":"2208.00231","title":"Masked Autoencoders As The Unified Learners For Pre-Trained Sentence Representation","created":"2022-07-30","cited_by_count":5,"area":null},{"id":"2210.17167","title":"Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives","created":"2022-10-31","cited_by_count":5,"area":null},{"id":"2304.03158","title":"CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrieval","created":"2023-04-05","cited_by_count":5,"area":null},{"id":"2306.11550","title":"Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency","created":"2023-06-05","cited_by_count":5,"area":null},{"id":"2311.03798","title":"Noisy Pair Corrector for Dense Retrieval","created":"2023-11-07","cited_by_count":5,"area":null},{"id":"2412.12505","title":"DocFusion: A Unified Framework for Document Parsing Tasks","created":"2024-12-17","cited_by_count":5,"area":null},{"id":"2504.05216","title":"Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling","created":"2025-04-07","cited_by_count":5,"area":null},{"id":"2206.13974","title":"Joint Generator-Ranker Learning for Natural Language Generation","created":"2022-06-28","cited_by_count":4,"area":null},{"id":"2210.15133","title":"Retrieval Oriented Masking Pre-training Language Model for Dense Passage Retrieval","created":"2022-10-27","cited_by_count":4,"area":null},{"id":"2212.09114","title":"CAPSTONE: Curriculum Sampling for Dense Retrieval with Document Expansion","created":"2022-12-18","cited_by_count":4,"area":null},{"id":"2212.10192","title":"Adam: Dense Retrieval Distillation with Adaptive Dark Examples","created":"2022-12-20","cited_by_count":4,"area":"distill"},{"id":"2312.02429","title":"PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models","created":"2023-12-05","cited_by_count":4,"area":null},{"id":"2401.00165","title":"Mitigating the Impact of False Negatives in Dense Retrieval with Contrastive Confidence Regularization","created":"2023-12-30","cited_by_count":4,"area":null},{"id":"2410.17243","title":"Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss","created":"2024-10-22","cited_by_count":4,"area":null},{"id":"2305.13197","title":"Challenging Decoder helps in Masked Auto-Encoder Pre-training for Dense Passage Retrieval","created":"2023-05-22","cited_by_count":3,"area":null},{"id":"2405.04545","title":"Learning label-label correlations in Extreme Multi-label Classification via Label Features","created":"2024-05-03","cited_by_count":3,"area":null},{"id":"2210.05521","title":"Hybrid Inverted Index Is a Robust Accelerator for Dense Retrieval","created":"2022-10-11","cited_by_count":2,"area":null},{"id":"2211.08769","title":"RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models","created":"2022-11-16","cited_by_count":2,"area":null},{"id":"2412.01443","title":"Multi-Facet Blending for Faceted Query-by-Example Retrieval","created":"2024-12-02","cited_by_count":2,"area":null},{"id":"2503.02922","title":"Optimizing open-domain question answering with graph-based retrieval augmented generation","created":"2025-03-04","cited_by_count":2,"area":"rag"},{"id":"2503.08161","title":"OASIS: Order-Augmented Strategy for Improved Code Search","created":"2025-03-11","cited_by_count":2,"area":null},{"id":"2510.09266","title":"CFVBench: A Comprehensive Video Benchmark for Fine-grained Multimodal Retrieval-Augmented Generation","created":"2025-10-10","cited_by_count":2,"area":"mllm"},{"id":"2205.16005","title":"Neural Retriever and Go Beyond: A Thesis Proposal","created":"2022-05-31","cited_by_count":1,"area":null},{"id":"2212.05225","title":"LEAD: Liberal Feature-based Distillation for Dense Retrieval","created":"2022-12-10","cited_by_count":1,"area":"distill"},{"id":"2304.05845","title":"Rethinking Dense Retrieval's Few-Shot Ability","created":"2023-04-12","cited_by_count":1,"area":null},{"id":"2403.14074","title":"M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence Retrieval","created":"2024-03-21","cited_by_count":1,"area":null},{"id":"2412.06099","title":"ENCO: Life-Cycle Management of Enterprise-Grade Copilots","created":"2024-12-08","cited_by_count":1,"area":null},{"id":"2507.11310","title":"LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification","created":"2025-07-15","cited_by_count":1,"area":"lr"},{"id":"2605.00505","title":"LLM-Oriented Information Retrieval: A Denoising-First Perspective","created":"2026-05-01","cited_by_count":1,"area":"rag"},{"id":"2305.09313","title":"Hybrid and Collaborative Passage Reranking","created":"2023-05-16","cited_by_count":0,"area":null},{"id":"2311.06444","title":"Mitigating Pooling Bias in E-commerce Search via False Negative Estimation","created":"2023-11-11","cited_by_count":0,"area":null},{"id":"2403.01999","title":"LLM-Oriented Retrieval Tuner","created":"2024-03-04","cited_by_count":0,"area":null},{"id":"2404.12152","title":"FecTek: Enhancing Term Weight in Lexicon-Based Retrieval with Feature Context and Term-level Knowledge","created":"2024-04-18","cited_by_count":0,"area":null},{"id":"2407.20083","title":"An Energy-based Model for Word-level AutoCompletion in Computer-aided Translation","created":"2024-07-29","cited_by_count":0,"area":null},{"id":"2508.11670","title":"RRRA: Resampling and Reranking through a Retriever Adapter","created":"2025-08-07","cited_by_count":0,"area":null},{"id":"2511.17417","title":"CREST: Improving Interpretability and Effectiveness of Troubleshooting at Ericsson through Criterion-Specific Trouble Report Retrieval","created":"2025-11-21","cited_by_count":0,"area":null},{"id":"2601.10837","title":"EncodeRec: An Embedding Backbone for Recommendation Systems","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2604.23336","title":"Efficient Rationale-based Retrieval: On-policy Distillation from Generative Rerankers based on JEPA","created":"2026-04-25","cited_by_count":0,"area":"distill"},{"id":"2605.27449","title":"Checking Fact with Better Retrieval: Dynamic Contrastive Learning for Evidence Retrieval","created":"2026-05-24","cited_by_count":0,"area":null}],"next_cursor":null}