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Retrieval-Augmented Generation (RAG) improves Large Language Models (LLMs) by retrieving supporting documents into the prompt, but existing methods do not explicitly target queries that require fetching multiple documents with substantially different content.
Passage Re-Ranking with BERT, April 2020
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Do Attention Heads in BERT Track Syntactic Dependencies?, November 2019
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History, Development, and Principles of Large Language Models: An Introductory Survey
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Investigation of Human Factors: The Link to Accident Prevention
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Columbia Accident Investigation Board Report , volume 2
Columbia Accident Investigation Board · 2003
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Designing and Evaluating a Human Factors Investigation Tool (HFIT) for Accident Analysis
Gordon, R., Flin, R., and Mearns, K · 2005
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Revisiting the Swiss Cheese Model of Accidents
Reason, J., Hollnagel, E., and Paries, J · 2006
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Reciprocal Rank Fusion Outperforms Condorcet and Individual Rank Learning Methods
Cormack, G. V., Clarke, C. L. A., and Buettcher, S · 2009
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The Probabilistic Relevance Framework: BM25 and Beyond
Robertson, S. and Zaragoza, H · 2009
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Transportation Accident Investigation: The Development of Human Factors Research and Practice
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Personalized Oncology: Recent Advances and Future Challenges
Kalia, M · 2012
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Developing an Effective Corrective Action Process: Lessons Learned from Operating a Confidential Close Call Reporting System
Multer, J., Ranney, J., Hile, J., Raslear, T., and John, A · 2013
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A Decision Support System for Total Airport Operations Management and Planning
Zografos, K. G., Madas, M. A., and Salouras, Y · 2013
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Collaborative Incident Analysis and Human Performance Handbook
Office of Railroad Safety · 2014
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A Full-Text Learning to Rank Dataset for Medical Information Retrieval
Boteva, V., Ghalandari, D. G., Sokolov, A., and Riezler, S · 2016
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Columbia Crew Survival Investigation Report
Packham, N. J · 2017
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Attention Is All You Need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
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Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models
Zhang, Y., Li, Y., Cui, L., Cai, D., Liu, L., Fu, T., Huang, X., Zhao, E., Zhang, Y., Chen, Y., Wang, L., Luu, A. T., Bi, W., Shi, F., and Shi, S · 2017
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Retrieval of the Best Counterargument without Prior Topic Knowledge
Wachsmuth, H., Syed, S., and Stein, B · 2018
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What Does BERT Look at? An Analysis of BERT’s Attention
Clark, K., Khandelwal, U., Levy, O., and Manning, C. D · 2019
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Multi-Head Attention with Diversity for Learning Grounded Multilingual Multimodal Representations
Huang, P.-Y., Chang, X., and Hauptmann, A · 2019
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Revealing the Dark Secrets of BERT
Kovaleva, O., Romanov, A., Rogers, A., and Rumshisky, A · 2019
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CEDR: Contextualized Embeddings for Document Ranking
MacAvaney, S., Yates, A., Cohan, A., and Goharian, N · 2019
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Are Sixteen Heads Really Better than One?
Michel, P., Levy, O., and Neubig, G · 2019
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Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Reimers, N. and Gurevych, I · 2019
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Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Voita, E., Talbot, D., Moiseev, F., Sennrich, R., and Titov, I · 2019
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Retrieval-Augmented Language Model Pre-Training
Guu, K., Lee, K., Tung, Z., Pasupat, P., and Chang, M.-W · 2020
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Poly-Encoders: Architectures and Pre-Training Strategies for Fast and Accurate Multi-Sentence Scoring
Humeau, S., Shuster, K., Lachaux, M.-A., and Weston, J · 2020
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ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
Khattab, O. and Zaharia, M · 2020
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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.-t., Rocktäschel, T., Riedel, S., and Kiela, D · 2020
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Document Ranking with a Pretrained Sequence-to-Sequence Model
Nogueira, R., Jiang, Z., Pradeep, R., and Lin, J · 2020
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MHSAN: Multi-Head Self-Attention Network for Visual Semantic Embedding
Park, G., Han, C., Yoon, W., and Kim, D · 2020
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Fact or Fiction: Verifying Scientific Claims
Wadden, D., Lin, S., Lo, K., Wang, L. L., van Zuylen, M., Cohan, A., and Hajishirzi, H · 2020
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Multi-Resolution Multi-Head Attention in Deep Speaker Embedding
Wang, Z., Yao, K., Li, X., and Fang, S · 2020
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A Guide to Human Factors in Accident Investigation
Bridger, R. S · 2021
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SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
Formal, T., Piwowarski, B., and Clinchant, S · 2021
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Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline
Gao, L., Dai, Z., and Callan, J · 2021
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Copy Suppression: Comprehensively Understanding a Motif in Language Model Attention Heads
McDougall, C. S., Conmy, A., Rushing, C., McGrath, T., and Nanda, N · 2024
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Vector Database Management Techniques and Systems
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Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
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RAG-Fusion: A New Take on Retrieval-Augmented Generation
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RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
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Detecting Pretraining Data from Large Language Models
Shi, W., Ajith, A., Xia, M., Huang, Y., Liu, D., Blevins, T., Chen, D., and Zettlemoyer, L · 2024
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Dense Hierarchical Retrieval for Open-Domain Question Answering
Liu, Y., Hashimoto, K., Zhou, Y., Yavuz, S., Xiong, C., and Yu, P · 2021
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End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering
Singh, D., Reddy, S., Hamilton, W., Dyer, C., and Yogatama, D · 2021
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Milvus: A Purpose-Built Vector Data Management System
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Updating Embeddings for Dynamic Knowledge Graphs, September 2021
Wewer, C., Lemmerich, F., and Cochez, M · 2021
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A Survey on Retrieval-Augmented Text Generation, February 2022
Li, H., Su, Y., Cai, D., Wang, Y., and Liu, L · 2022
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In-Context Learning and Induction Heads, September 2022
Olsson, C., Elhage, N., Nanda, N., Joseph, N., DasSarma, N., Henighan, T., Mann, B., Askell, A., Bai, Y., Chen, A., Conerly, T., Drain, D., Ganguli, D., Hatfield-Dodds, Z., Hernandez, D., Johnston, S., Jones, A., Kernion, J., Lovitt, L., Ndousse, K., Amodei, D., Brown, T., Clark, J., Kaplan, J., McCandlish, S., and Olah, C · 2022
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ESPN: Memory-Efficient Multi-Vector Information Retrieval
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Wang, L., Yang, N., Huang, X., Jiao, B., Yang, L., Jiang, D., Majumder, R., and Wei, F · 2024
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ORAG: Ontology-Guided Retrieval-Augmented Generation for Theme-Specific Entity Typing
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Benchmarking Retrieval-Augmented Generation for Medicine
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Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
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Federated Recommendation via Hybrid Retrieval Augmented Generation
Zeng, H., Yue, Z., Jiang, Q., and Wang, D · 2024
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CheckEmbed: Effective Verification of LLM Solutions to Open-Ended Tasks, July 2025
Besta, M., Paleari, L., Copik, M., Gerstenberger, R., Kubicek, A., Nyczyk, P., Iff, P., Schreiber, E., Srindran, T., Lehmann, T., Niewiadomski, H., and Hoefler, T · 2025
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From Local to Global: A Graph RAG Approach to Query-Focused Summarization, February 2025
Edge, D., Trinh, H., Cheng, N., Bradley, J., Chao, A., Mody, A., Truitt, S., Metropolitansky, D., Ness, R. O., and Larson, J · 2025
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Hu, Y. and Lu, Y · 2025
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Retrieval-Augmented Generation with Hierarchical Knowledge
Huang, H., Huang, Y., Junjie, Y., Pan, Z., Chen, Y., Ma, K., Chen, H., and Cheng, J · 2025
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NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models
Lee, C., Roy, R., Xu, M., Raiman, J., Shoeybi, M., Catanzaro, B., and Ping, W · 2025
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CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models
Lyu, Y., Li, Z., Niu, S., Xiong, F., Tang, B., Wang, W., Wu, H., Liu, H., Xu, T., and Chen, E · 2025
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A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge, June 2025
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Parametric Retrieval Augmented Generation
Su, W., Tang, Y., Ai, Q., Yan, J., Wang, C., Wang, H., Ye, Z., Zhou, Y., and Liu, Y · 2025
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SUNAR: Semantic Uncertainty Based Neighborhood Aware Retrieval for Complex QA
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Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient
Wang, G., Hoogland, J., van Wingerden, S., Furman, Z., and Murfet, D · 2025
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Hallucination is Inevitable: An Innate Limitation of Large Language Models, February 2025
Xu, Z., Jain, S., and Kankanhalli, M · 2025
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On Protecting the Data Privacy of Large Language Models (LLMs) and LLM Agents: A Literature Review
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SuperRAG: Beyond RAG with Layout-Aware Graph Modeling
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MoC: Mixtures of Text Chunking Learners for Retrieval-Augmented Generation System
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Massive Text Embeddings Benchmark Leaderboard, 2026
Huggingface · 2026
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Retrieval-Augmented Generation for AI-Generated Content: A Survey
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