https://github.com/lcfractal/tgdt
Efficient Token-Guided Image-Text Retrieval with Consistent Multimodal Contrastive Training
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/lebrosoft/hnswlib_0.3_leon
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors
https://github.com/lebrosoft/hnswlib_new
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors
https://github.com/ledmaster/swing
Large Scale Product Graph Construction for Recommendation in E-commerce
https://github.com/leehangyu/MultiGrain_Application
MultiGrain: a unified image embedding for classes and instances
https://github.com/leftthomas/CGD
Combination of Multiple Global Descriptors for Image Retrieval
https://github.com/leokarlin/LaSO
LaSO: Label-Set Operations networks for multi-label few-shot learning
https://github.com/leolee99/2022-neurips-daa
https://github.com/leolee99/CLIP_ITM
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/beit
https://github.com/leonty1/deepldnn
https://github.com/leonty1/essm
https://github.com/leosampaio/sketchformer
Sketchformer: Transformer-based Representation for Sketched Structure
https://github.com/leule/DCDS
https://github.com/levon003/wiki-ores-feedback
https://github.com/lex-lingo/lingo
https://github.com/lichengunc/pretrain-vl-data
https://github.com/lighterswang/biomedclip-lora
https://github.com/lightonai/pylate
https://github.com/lihenglin/bridge_training_code
FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation Learning
https://github.com/liliaellouz/wabi-sabi
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/linjieli222/hero_video_feature_extractor
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
https://github.com/liuziwei7/fashion-landmarks
https://github.com/liyan06/minicheck
RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models
https://github.com/liyinxiao/UnifiedEmbeddingModel
https://github.com/lizhemin15/self-distillation
https://github.com/locuslab/projected_sinkhorn
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
https://github.com/lolrudy/rbp_pose
GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting
https://github.com/lsh110600/person_re_id
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/lucas-dunker/stem-separator-amt
https://github.com/lucidrains/CoCa-pytorch
CoCa: Contrastive Captioners are Image-Text Foundation Models
https://github.com/lucidrains/RETRO-pytorch
Current Limitations of Language Models: What You Need is Retrieval
https://github.com/lucidrains/infini-transformer-pytorch
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
https://github.com/lucidrains/mammut-pytorch
MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks
https://github.com/lucidrains/marge-pytorch
https://github.com/lucidrains/mlm-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.