Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 11
- 보존된 평가 기록
- 19
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/yihongl1u/colexificationnet
공식 코드https://github.com/yihshe/ai-refined-rtm
공식 코드From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer Model
https://github.com/yihuaihong/dissecting-ft-unlearning
공식 코드https://github.com/yilinjz/astchunk
공식 코드https://github.com/yimuwangcs/Better_Cross_Modal_Retrieval
공식 코드Video-Text Retrieval by Supervised Sparse Multi-Grained Learning
https://github.com/yingift/mstar
공식 코드MSTAR: Box-free Multi-query Scene Text Retrieval with Attention Recycling
https://github.com/yinjiehuang/StarSHL
공식 코드https://github.com/yinzhangyue/c2fm
공식 코드https://github.com/yinzhangyue/smoothing-r3
공식 코드https://github.com/yixiangch/mrd-rag
공식 코드MRD-RAG: Enhancing Medical Diagnosis with Multi-Round Retrieval-Augmented Generation
https://github.com/yixuantt/MultiHop-RAG
공식 코드MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries
https://github.com/yixuantt/poolingandattn
공식 코드Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?
https://github.com/yizhen20133868/Retriever-Dialogue
공식 코드Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever
https://github.com/yjeugenia/maferw
공식 코드MaFeRw: Query Rewriting with Multi-Aspect Feedbacks for Retrieval-Augmented Large Language Models
https://github.com/yjsoh/youra
공식 코드You Only Use Reactive Attention Slice For Long Context Retrieval
https://github.com/ykumards/eclip
공식 코드Improving Medical Multi-modal Contrastive Learning with Expert Annotations
https://github.com/yl-1993/learn-to-cluster
공식 코드Learning to Cluster Faces via Confidence and Connectivity Estimation
https://github.com/ylsung/vl-merging
공식 코드https://github.com/ymcidence/DeepSketchHashing
공식 코드Deep Sketch Hashing: Fast Free-hand Sketch-Based Image Retrieval
https://github.com/ymcidence/TBH
공식 코드https://github.com/ymgw55/cosine-similarity-via-ica
공식 코드Revisiting Cosine Similarity via Normalized ICA-transformed Embeddings
https://github.com/ynchuang/discoverpath
공식 코드https://github.com/yny0506/massive-videos-moment-retrieval
공식 코드https://github.com/yoega/mor
공식 코드Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases
https://github.com/yohanjo/kenli
공식 코드Knowledge-Enhanced Evidence Retrieval for Counterargument Generation
https://github.com/yoichi1484/subspace
공식 코드Subspace Representations for Soft Set Operations and Sentence Similarities
https://github.com/yongchao97/diffusion_inversion
공식 코드Training on Thin Air: Improve Image Classification with Generated Data
https://github.com/yookoon/nac
공식 코드Unsupervised Representation Learning via Neural Activation Coding
https://github.com/yoonkicho/pplr
공식 코드Part-based Pseudo Label Refinement for Unsupervised Person Re-identification
https://github.com/youngerous/qtree
공식 코드Learning to Explore and Select for Coverage-Conditioned Retrieval-Augmented Generation
https://github.com/youngkyunJang/GPQ
공식 코드Generalized Product Quantization Network for Semi-supervised Image Retrieval
https://github.com/youngkyunjang/deep-hash-distillation
공식 코드https://github.com/youngkyunjang/spq
공식 코드Self-supervised Product Quantization for Deep Unsupervised Image Retrieval
https://github.com/youngminPIL/AutoLR
공식 코드AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks
https://github.com/ypapanik/biomedical-slot-filling
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.