https://github.com/AnnaNikitaRL/EVA
Fast deep reinforcement learning using online adjustments from the past
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 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/Aolin-MIR/Sequence-to-Sequence-Piano-Transcription-with-Transformers
https://github.com/Ariel-Perez/triplet-net
https://github.com/ArionDas/Generative_AI_Research
Retrieval-Augmented Generation for AI-Generated Content: A Survey
https://github.com/ArionDas/InfiniGPT
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
https://github.com/ArsenalCheng/Meta-Adapter
Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification
https://github.com/ArturPrzybysz/MNIST-siamese
https://github.com/ArvinZhuang/DSI-transformers
https://github.com/Ash-Lee233/delf
Large-Scale Image Retrieval with Attentive Deep Local Features
https://github.com/Atomu2014/product-nets
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
https://github.com/Attn-to-FC/Attn-to-FC
code2seq: Generating Sequences from Structured Representations of Code
https://github.com/AyanKumarBhunia/on-the-fly-FGSBIR
Sketch Less for More: On-the-Fly Fine-Grained Sketch Based Image Retrieval
https://github.com/AyanKumarBhunia/semisupervised-FGSBIR
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
https://github.com/BAJUKA/SQuAD-NLP
https://github.com/BPYap/Question-Generation
Ask the Right Questions: Active Question Reformulation with Reinforcement Learning
https://github.com/BSlience/end2end-conversational-ai
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/Babylonpartners/fastText_multilingual
Improving zero-shot learning by mitigating the hubness problem
https://github.com/BaladityaY/lemniscate_reproduce_bdd
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
https://github.com/BaladityaY/lemniscate_vis
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
https://github.com/BenjaminLiuPenrose/UnsupervisedImage
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
https://github.com/BenoitTran/END
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
https://github.com/Beomi/InfiniTransformer
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
https://github.com/BestJuly/IIC
Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework
https://github.com/BestJuly/VCP
Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning
https://github.com/BinaryWiz/UPM
A Clustering-Based Combinatorial Approach to Unsupervised Matching of Product Titles
https://github.com/BinaryWiz/Unsupervised-Product-Matching-Using-Combinations-and-Permutations
A Clustering-Based Combinatorial Approach to Unsupervised Matching of Product Titles
https://github.com/Bingo-W/Personalisation-in-LLM
https://github.com/BonaventureR/person-reid
https://github.com/BoseungJeong/ASMR-ICCV-2021
Improving Person Re-identification by Attribute and Identity Learning
https://github.com/BryanPlummer/cite
Learning Two-Branch Neural Networks for Image-Text Matching Tasks
https://github.com/C0sch0/lecturasIIC3633-2021
Deep Learning based Recommender System: A Survey and New Perspectives
https://github.com/CAPTEteam/annotation-tool-segmentation
https://github.com/CAS-CLab/K-Nearest-Neighbors-Hashing
https://github.com/CP8315-NNP-JLOPEZ/NNP-Chatbot
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/Calylyli/PCB_RPP
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/CarlsonZhuo/primal_dual_frank_wolfe
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.