https://github.com/ll0ruc/AutoMIR
공식 코드AutoMIR: Effective Zero-Shot Medical Information Retrieval without Relevance Labels
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/ll0ruc/ada-retrieval
공식 코드Ada-Retrieval: An Adaptive Multi-Round Retrieval Paradigm for Sequential Recommendations
https://github.com/llm-lab-org/CLASP
공식 코드CLASP: Contrastive Language-Speech Pretraining for Multilingual Multimodal Information Retrieval
https://github.com/llm-lab-org/multimodal-rag-survey
공식 코드Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation
https://github.com/llm-vlm-gsl/discuss-rag
공식 코드Talk Before You Retrieve: Agent-Led Discussions for Better RAG in Medical QA
https://github.com/llm4eval/LLMJudge
공식 코드https://github.com/lluisgomez/TextTopicNet
공식 코드https://github.com/lluisgomez/single-shot-str
공식 코드https://github.com/lmbxmu/mycode
공식 코드Towards Optimal Discrete Online Hashing with Balanced Similarity
https://github.com/lmh0921/keyb
공식 코드The Power of Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
https://github.com/lmmapplication/rakg
공식 코드RAKG:Document-level Retrieval Augmented Knowledge Graph Construction
https://github.com/lntzm/mesm
공식 코드Towards Balanced Alignment: Modal-Enhanced Semantic Modeling for Video Moment Retrieval
https://github.com/lockon-n/self-prompting
공식 코드Self-Prompting Large Language Models for Zero-Shot Open-Domain QA
https://github.com/lolrudy/gpv_pose
공식 코드GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting
https://github.com/lolrudy/kp-red
공식 코드KP-RED: Exploiting Semantic Keypoints for Joint 3D Shape Retrieval and Deformation
https://github.com/longkukuhi/multiway-adapter
공식 코드MultiWay-Adapater: Adapting large-scale multi-modal models for scalable image-text retrieval
https://github.com/longtaojiang/seds
공식 코드SEDS: Semantically Enhanced Dual-Stream Encoder for Sign Language Retrieval
https://github.com/lorelupo/divide-and-rule
공식 코드Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models
https://github.com/lorenmt/vsl
공식 코드https://github.com/losercheems/doge
공식 코드Wonderful Matrices: Combining for a More Efficient and Effective Foundation Model Architecture
https://github.com/losercheems/wonderfulmatrices
공식 코드Wonderful Matrices: Combining for a More Efficient and Effective Foundation Model Architecture
https://github.com/louis-bahrman/inpainting-fourier
공식 코드https://github.com/louisdo/eru-kg
공식 코드ERU-KG: Efficient Reference-aligned Unsupervised Keyphrase Generation
https://github.com/love481/Cross-modal-Contrastive-Learning-with-Asymmetric-Co-attention-Network-for-Video-Moment-Retrieval
공식 코드Cross-modal Contrastive Learning with Asymmetric Co-attention Network for Video Moment Retrieval
https://github.com/lovelyhan/zoomer
공식 코드ZOOMER: Boosting Retrieval on Web-scale Graphs by Regions of Interest
https://github.com/lowlevelai/glare
공식 코드GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook Retrieval
https://github.com/lporcaro/music-diversity-analysis
공식 코드https://github.com/lsh0520/3d-molm
공식 코드https://github.com/lsusman/stable-memory
공식 코드https://github.com/lsx-uniwue/background-bias-in-dml
공식 코드https://github.com/lsx-uniwue/indirect
공식 코드InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images
https://github.com/ltgoslo/brent
공식 코드BRENT: Bidirectional Retrieval Enhanced Norwegian Transformer
https://github.com/ltgoslo/more-room-for-language
공식 코드More Room for Language: Investigating the Effect of Retrieval on Language Models
https://github.com/lttsmn/LXMERT-S
공식 코드Multi-stage Pre-training over Simplified Multimodal Pre-training Models
https://github.com/ltttpku/ada-cm
공식 코드Efficient Adaptive Human-Object Interaction Detection with Concept-guided Memory
https://github.com/ltzheng/synapse
공식 코드Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.