Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/iCompass-ai/TunBERT
https://github.com/iMoonLab/MeshNet
https://github.com/iYiYaHa/PyTorch-IRGAN
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
https://github.com/ibm-self-serve-assets/metagen-blended-rag
MetaGen Blended RAG: Higher Accuracy for Domain-Specific Q&A Without Fine-Tuning
https://github.com/icoz69/DeepEMD
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
https://github.com/idejie/SCAN
https://github.com/idsia/modern-srwm
https://github.com/idsia/neuraldiffeq-fwp
https://github.com/iesl/geometric_graph_embedding
https://github.com/iinemo/lm-polygraph
Enhancing Uncertainty-Based Hallucination Detection with Stronger Focus
https://github.com/iit-nlp-research/chatgpt-crawler
https://github.com/ilias-vrg/ilias
https://github.com/illuin-tech/colpali
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/illuin-tech/grouse
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/ilmonteux/logohunter
https://github.com/ilyassmoummad/ProtoCLR
BIRB: A Generalization Benchmark for Information Retrieval in Bioacoustics
https://github.com/imamathcat/LASER_Dependencies
Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
https://github.com/imatge-upc/salbow
Saliency Weighted Convolutional Features for Instance Search
https://github.com/immuno121/audio_source_classification
https://github.com/inclusionai/aworld
RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism
https://github.com/informagi/REL
https://github.com/innat/DOLG-TensorFlow
DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features
https://github.com/insikk/delf_enhanced
Large-Scale Image Retrieval with Attentive Deep Local Features
https://github.com/inspire-group/RobustRAG
https://github.com/intellabs/fastrag
https://github.com/interestingzhuo/foodretreival
Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval
https://github.com/internlm/huixiangdou
https://github.com/iooops/CS221-Audio-Tagging
Deep convolutional neural networks for predominant instrument recognition in polyphonic music
https://github.com/irgroup/clef2023-longeval-irc
https://github.com/irgroup/ir_metadata
ir_metadata: An Extensible Metadata Schema for IR Experiments
https://github.com/ishandutta2007/Craft
https://github.com/ispamm/htorch
https://github.com/ivclab/cvs
On the Exploration of Incremental Learning for Fine-grained Image Retrieval
https://github.com/ivendrov/order-embedding
https://github.com/ivychill/reid
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.