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/yeounoh/lc_nl2sql
https://github.com/yerevann/chemlactica
https://github.com/ygryadit/Towards3DVRSketch
https://github.com/yhshu/distribution-shifts-for-kbqa
TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge Bases
https://github.com/yingyichen-cyy/Nested-Co-teaching
Boosting Co-teaching with Compression Regularization for Label Noise
https://github.com/yinyuan1227/strap-git
https://github.com/ymcidence/Zero-Shot-Sketch-Image-Hashing
https://github.com/ymcui/chinese-llama-alpaca-2
Extending Context Window of Large Language Models via Positional Interpolation
https://github.com/yolo2233/cross-modal-hasing-playground
https://github.com/yongqyu/ranking_paragraphs_pytorch
Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answering
https://github.com/youqingxiaozhua/abaw5
Unsupervised Facial Expression Representation Learning with Contrastive Local Warping
https://github.com/ypeleg/komplex
https://github.com/yrobink/SBCK
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
https://github.com/ysglh/Task-Oriented-Dialogue-Dataset-Survey
https://github.com/yudhik11/MER-lyrics-Transformer
Transformer-based approach towards music emotion recognition from lyrics
https://github.com/yujiacheng333/CircleLossMNIST
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/yujiapingyu/Deep-Hashing
Feature Learning based Deep Supervised Hashing with Pairwise Labels
https://github.com/yukayo/lotnext
Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation
https://github.com/yuleiniu/rva
https://github.com/yuliangcai2022/clumo
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
https://github.com/yunhak0/muse
https://github.com/yurymalkov/hnsw
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors
https://github.com/yxgeee/openibl
NetVLAD: CNN architecture for weakly supervised place recognition
https://github.com/yzspku/CQTNet
Learning a Representation for Cover Song Identification Using Convolutional Neural Network
https://github.com/zfj1998/CodeBert-Code2Text
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
https://github.com/zhangcheng-007/Stochastic_Generative_Hashing
https://github.com/zhangxinyu-xyz/PGAN-VehicleRe-ID
Part-Guided Attention Learning for Vehicle Instance Retrieval
https://github.com/zhaoolee/garss
DeepRAG: Thinking to Retrieval Step by Step for Large Language Models
https://github.com/zhaoyue-zephyrus/avion
https://github.com/zhen8838/Circle-Loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/zhengxujosh/awesome-rag-vision
Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook
https://github.com/zhihaozhang97/ru-ai
https://github.com/zhixinlai/llmboostmedical
Frozen Transformers in Language Models Are Effective Visual Encoder Layers
https://github.com/zhongpeixiang/ckc
https://github.com/zhoujiahuan1991/cvpr2025-stop
DGL: Dynamic Global-Local Prompt Tuning for Text-Video Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.