https://github.com/HuiDingUMD/ExprGAN
ExprGAN: Facial Expression Editing with Controllable Expression Intensity
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/IDSIA/lmtool-fwms
https://github.com/IDSIA/lmtool-fwp
https://github.com/IDSIA/recurrent-fwp
https://github.com/IISCAditayTripathi/SketchGuidedLocalization
https://github.com/IMvision12/keras-vision-models
https://github.com/INK-USC/MHGRN
https://github.com/INK-USC/RE-Net
https://github.com/Inria-Chile/risotto
https://github.com/IntelLabs/Optimized-Implementation-of-Word-Movers-Distance
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
https://github.com/InternLM/opencompass
NeedleBench: Can LLMs Do Retrieval and Reasoning in Information-Dense Context?
https://github.com/IsaacChanghau/ReLoCLNet
https://github.com/IzabelaKrupinska/PROJBAD
Deep Visual-Semantic Alignments for Generating Image Descriptions
https://github.com/JasonForJoy/BERT-for-Response-Selection
Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots
https://github.com/Jeffyrao/neural-tweet-search
Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search
https://github.com/JeremyFisher/deep_level_sets
Learning a Predictable and Generative Vector Representation for Objects
https://github.com/JeremyFisher/few_shot_3dr
Learning a Predictable and Generative Vector Representation for Objects
https://github.com/JerryKwon/melon_plylst_continuation
Neural Collaborative Filtering vs. Matrix Factorization Revisited
https://github.com/JesperDramsch/keras-complex
https://github.com/JiabenLi/rgcn_paddlepaddle
https://github.com/JiaquanYe/TableMASTER-mmocr
https://github.com/JunjieHu/xtreme-dev
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
https://github.com/JunweiLiang/aicity_action
https://github.com/KeLi-SketchX/Universal-sketch-perceptual-grouping
https://github.com/Kelechukwu1/PidginUNMT
Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion
https://github.com/KhueNguyen312/Persona-Chatbot
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/Kso-Ayaka/MS_Paperwithcode/tree/main/Attribute-Aware%20Deep%20Hashing
Attribute-Aware Deep Hashing with Self-Consistency for Large-Scale Fine-Grained Image Retrieval
https://github.com/KubotaYugo/Impression-CLIP-Contrastive-Shape-Impression-Embedding-for-Fonts
Impression-CLIP: Contrastive Shape-Impression Embedding for Fonts
https://github.com/KyGao/token-level-classification
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
https://github.com/LADI-Dataset/ladi-overview
https://github.com/LDVC124/2016_person_re-ID
A Discriminatively Learned CNN Embedding for Person Re-identification
https://github.com/LONG-9621/IQA01
Image Quality Assessment: Unifying Structure and Texture Similarity
https://github.com/LONG-9621/SO-Net
https://github.com/LRegan666/Tree_Deep_Model
https://github.com/LavieLuo/DRA
Discriminative Residual Analysis for Image Set Classification with Posture and Age Variations
https://github.com/LawrenceDuan/myLASER
Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.