MoRAG -- Multi-Fusion Retrieval Augmented Generation for Human Motion
专题命中 检索器与排序 :retrieval augmented generation(title);retrieval-augmented generation(abstract);RAG(abstract)
AI 大模型
检索增强生成、向量检索、知识库问答和面向大模型的搜索系统。
专题命中 检索器与排序 :retrieval augmented generation(title);retrieval-augmented generation(abstract);RAG(abstract)
专题命中 检索器与排序 :retrieval augmented generation(title,abstract);RAG(abstract)
Comments 9 pages, 4 figures
专题命中 检索器与排序 :retrieval-augmented generation(title);retrieval augmented generation(abstract);RAG(abstract)
Comments 10 pages, 4 figures
专题命中 检索器与排序 :retrieval augmented generation(title);retrieval-augmented generation(abstract);RAG(abstract)
专题命中 检索器与排序 :retrieval-augmented generation(title,abstract);RAG(abstract)
专题命中 检索器与排序 :retriever(title);dense retrieval(abstract);分类 cs.IR、cs.CL、cs.AI
Comments 8 pages, references at pp7,8; EMNLP workshop submission
专题命中 检索器与排序 :retrieval-augmented generation(title,abstract);RAG(abstract)
Comments To appear in USENIX Security Symposium 2025. The code is available at https://github.com/sleeepeer/PoisonedRAG
专题命中 检索器与排序 :retrieval augmented generation(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments Paper published at Machine Learning for Healthcare 2024 (MLHC'24)
专题命中 检索器与排序 :RAG(title,abstract);retrieval augmented generation(abstract)
专题命中 检索器与排序 :RAG(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments Accepted to ICML 2024
专题命中 检索器与排序 :retrieval-augmented generation(title,abstract);RAG(abstract)
专题命中 检索器与排序 :dense retrieval(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments Under Reivew
专题命中 检索器与排序 :retrieval augmented generation(title);retrieval-augmented generation(abstract);RAG(abstract)
Comments 7 pages, 2 figures, 3 tables
专题命中 检索器与排序 :retrieval augmented generation(title);retriever(abstract);分类 cs.IR、cs.CL、cs.AI
Comments AAAI 2024 (Association for the Advancement of Artificial Intelligence) Scientific Document Understanding Workshop
专题命中 检索器与排序 :RAG(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments 16 pages
专题命中 检索器与排序 :dense retrieval(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments Accepted at NAACL 2024. Data released at https://github.com/google-research-datasets/swim-ir
专题命中 检索器与排序 :retrieval-augmented generation(title);RAG(abstract);分类 cs.IR、cs.CL、cs.AI
Comments 11 page Workshop paper, AAAI2024 Workshop on AI for Education - Bridging Innovation and Responsibility, Large Language Model, Personalized Tutor Training, Automatic Assessment
专题命中 检索器与排序 :retrieval augmented generation(title,abstract);RAG(abstract)
Comments 6 pages
专题命中 检索器与排序 :retrieval-augmented generation(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments Accepted by WWW 2024
专题命中 检索器与排序 :retrieval-augmented generation(title);retriever(abstract);分类 cs.IR、cs.CL、cs.AI
Comments Accepted by ECIR2024 full paper
专题命中 检索器与排序 :retrieval-augmented generation(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments Deep Generative Models for Health Workshop NeurIPS 2023
专题命中 检索器与排序 :dense retrieval(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments EMNLP 2023 (Findings)
专题命中 检索器与排序 :dense retrieval(title,abstract);分类 cs.IR、cs.CL、cs.AI
专题命中 检索器与排序 :retriever(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments 9 pages, accepted by AAAI 2023
专题命中 检索器与排序 :retriever(title,abstract);knowledge retrieval(abstract)
专题命中 检索器与排序 :retrieval augmented generation(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments Accepted at EMNLP 2021. arXiv admin note: substantial text overlap with arXiv:2104.08610
专题命中 检索器与排序 :retriever(title,abstract);分类 cs.IR、cs.CL、cs.AI
Comments 10 pages, accepted to Findings of EMNLP 2021
专题命中 检索器与排序 :RAG(title,abstract);分类 cs.CL、cs.AI
Comments LLM;RAG;MCTS
专题命中 检索器与排序 :RAG(title,comments);retrieval-augmented generation(abstract);分类 cs.IR、cs.CL
Comments Accepted for the 1st Workshop on GenAI and RAG Systems for Enterprise @ CIKM 2024
专题命中 检索器与排序 :retriever(title,abstract);分类 cs.IR、cs.CL
Comments Accepted for presentation at the International Joint Conference on Neural Networks (IJCNN) 2018
Journal ref A. H. C. Correia, J. L. M. Silva, T. d. C. Martins and F. G. Cozman, "A Fully Attention-Based Information Retriever," 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, 2018, pp. 2799-2806