Retrieval
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A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/xhluca/bm25-benchmarks
BM25S: Orders of magnitude faster lexical search via eager sparse scoring
https://github.com/xiangyue9607/CliniRC
https://github.com/xiaobaicxy/SMN_Multi_Turn_Response_Selection_Pytorch
https://github.com/xiaomin418/cfsum
https://github.com/xiaoqian-shen/StoryGPT-V
https://github.com/xiaoxiong74/face-cluster-by-infomap
Learning to Cluster Faces via Confidence and Connectivity Estimation
https://github.com/xieh97/dcase2022-audio-retrieval
https://github.com/xikai97/med-mim
https://github.com/xingyuansun/pix3d
Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling
https://github.com/xingyuliuNLP/ResponseEdit_FR
Two are Better than One: An Ensemble of Retrieval- and Generation-Based Dialog Systems
https://github.com/xinyandai/pnsw
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors
https://github.com/xlang-ai/instructor-embedding
One Embedder, Any Task: Instruction-Finetuned Text Embeddings
https://github.com/xnancy/convai-transformer
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/xrenaa/Human-Motion-Analysis-with-Deep-Metric-Learning
https://github.com/xue-pai/FuxiCTR
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
https://github.com/xuxu116/pytorch-reid-lite
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/xxworkspace/hnswlib
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors
https://github.com/xypeng9903/k-diffusion-inverse-problems
Diffusion Posterior Sampling for General Noisy Inverse Problems
https://github.com/y-ding/nurd-mlsys22-code
https://github.com/yachae/hello-world
https://github.com/yalesong/pvse
Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval
https://github.com/yalsaffar/S-COLBERT
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
https://github.com/yang-ze-kang/PassageReranking
https://github.com/yangjianxin1/longqlora
Extending Context Window of Large Language Models via Positional Interpolation
https://github.com/yangyucheng000/MSpaper/tree/main/u2net
Res-U2Net: Untrained Deep Learning for Phase Retrieval and Image Reconstruction
https://github.com/yangyucheng000/Papers/tree/main/MindSpore-Retrieval-augmented
https://github.com/yangyucheng000/University/tree/main/model-3/rag
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/yangzhao1230/graphtextretrieval
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language
https://github.com/yasar-rehman/fedvssl
https://github.com/ybayle/ISM2017
Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook
https://github.com/ybayle/ReproducibleResearchCode
Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook
https://github.com/ybayle/SMC2017
Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook
https://github.com/ycao5602/SAL
Improving Person Re-identification by Attribute and Identity Learning
https://github.com/ycxioooong/MovieSynopsisAssociation
Person Search in Videos with One Portrait Through Visual and Temporal Links
https://github.com/yeliudev/R2-Tuning
QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.