Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 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/medtray/StruBERT
공식 코드StruBERT: Structure-aware BERT for Table Search and Matching
https://github.com/meetelise/surprise-similarity
공식 코드https://github.com/meettyj/gnp
공식 코드https://github.com/meettyj/recipe2vec
공식 코드Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks
https://github.com/mega002/DocQN
공식 코드Learning to Search in Long Documents Using Document Structure
https://github.com/megagonlabs/cypherbench
공식 코드CypherBench: Towards Precise Retrieval over Full-scale Modern Knowledge Graphs in the LLM Era
https://github.com/megagonlabs/sato
공식 코드https://github.com/megagonlabs/witqa
공식 코드https://github.com/megamine25/Music-genre-classification
공식 코드https://github.com/megayeye/triangle-net
공식 코드https://github.com/mehdi-mbl/WordCoding
공식 코드https://github.com/mehdiazarafza/uav-rag
공식 코드https://github.com/mehrdadsaberi/drew
공식 코드DREW : Towards Robust Data Provenance by Leveraging Error-Controlled Watermarking
https://github.com/mengcaopku/locvtp
공식 코드https://github.com/mengdanzhu/cross-modal-rag
공식 코드Cross-modal RAG: Sub-dimensional Retrieval-Augmented Text-to-Image Generation
https://github.com/mengshor/JTAV
공식 코드https://github.com/menidata1/mimic_2_omop
공식 코드https://github.com/mercatorhq/dubo-sql
공식 코드Dubo-SQL: Diverse Retrieval-Augmented Generation and Fine Tuning for Text-to-SQL
https://github.com/merlresearch/ranf-hrtf
공식 코드Retrieval-Augmented Neural Field for HRTF Upsampling and Personalization
https://github.com/merschformann/RAWSim-O
공식 코드https://github.com/mertyg/vision-language-models-are-bows
공식 코드When and why vision-language models behave like bags-of-words, and what to do about it?
https://github.com/meshidenn/cai
공식 코드Unsupervised Domain Adaptation for Sparse Retrieval by Filling Vocabulary and Word Frequency Gaps
https://github.com/mesnico/TERAN
공식 코드Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders
https://github.com/mesnico/TERN
공식 코드Transformer Reasoning Network for Image-Text Matching and Retrieval
https://github.com/mesnico/aladin
공식 코드ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and Retrieval
https://github.com/mesnico/idclip
공식 코드Towards Identity-Aware Cross-Modal Retrieval: a Dataset and a Baseline
https://github.com/mesnico/text-to-motion-retrieval
공식 코드Text-to-Motion Retrieval: Towards Joint Understanding of Human Motion Data and Natural Language
https://github.com/metemaad/TrajLib
공식 코드On feature selection and evaluation of transportation mode prediction strategies
https://github.com/metildachee/persrv
공식 코드PerSRV: Personalized Sticker Retrieval with Vision-Language Model
https://github.com/metra4ok/hpointloc
공식 코드HPointLoc: Point-based Indoor Place Recognition using Synthetic RGB-D Images
https://github.com/mever-team/ausil
공식 코드Audio-based Near-Duplicate Video Retrieval with Audio Similarity Learning
https://github.com/mever-team/distill-and-select
공식 코드DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
https://github.com/mi92/reverse-image-rag
공식 코드Reverse Image Retrieval Cues Parametric Memory in Multimodal LLMs
https://github.com/mic-dkfz/foundation-models-for-cbmir
공식 코드Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology
https://github.com/miccunifi/circo
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.