https://github.com/JasonForJoy/DIM
공식 코드Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based Chatbots
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/JasonForJoy/FIRE
공식 코드https://github.com/JasonForJoy/IMN
공식 코드Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
https://github.com/JasonForJoy/Personalized-Response-Selection
공식 코드https://github.com/JasonForJoy/SA-BERT
공식 코드Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots
https://github.com/JasonForJoy/U2U-IMN
공식 코드https://github.com/Jeff-Zilence/Explain_Metric_Learning
공식 코드https://github.com/Jeffyrao/TREC-Microblog-Datasets
공식 코드Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search
https://github.com/Jiamian-Wang/HSI_baseline
공식 코드A Simple and Efficient Reconstruction Backbone for Snapshot Compressive Imaging
https://github.com/JiapengL/multi_ling_search
공식 코드https://github.com/JiapengWu/Time-Aware-Incremental-Embedding
공식 코드TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
https://github.com/Jihuai-wpy/bert-ancient-chinese
공식 코드The Uncertainty-based Retrieval Framework for Ancient Chinese CWS and POS
https://github.com/JingbiaoMei/RGCL
공식 코드Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning
https://github.com/JingfenQiao/ColPali-Reproducibility
공식 코드Reproducibility, Replicability, and Insights into Visual Document Retrieval with Late Interaction
https://github.com/Jinjiarui/DRSR
공식 코드https://github.com/JohnGiorgi/DeCLUTR
공식 코드DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations
https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/1.4.Biomedical_NER_SparkNLP_paper_reproduce.ipynb
공식 코드https://github.com/JorgeGabin/ColBERTKP
공식 코드https://github.com/JoyDajunSpaceCraft/RAG-RLRC-LaySum
공식 코드https://github.com/JuanDuGit/DH3D
공식 코드DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization
https://github.com/Jun-jie-Huang/WhiteningBERT
공식 코드WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach
https://github.com/JuseonDo/DL-MMR
공식 코드Considering Length Diversity in Retrieval-Augmented Summarization
https://github.com/JustinHsu1019/KAP
공식 코드KAP: MLLM-assisted OCR Text Enhancement for Hybrid Retrieval in Chinese Non-Narrative Documents
https://github.com/KID-7391/seeking-the-shape-of-sound
공식 코드Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association
https://github.com/KU-CVLAB/RetDream
공식 코드Retrieval-Augmented Score Distillation for Text-to-3D Generation
https://github.com/KaiyangZhou/Dassl.pytorch
공식 코드https://github.com/KaiyangZhou/mixstyle-release
공식 코드https://github.com/KanghoonYoon/torch-rasgg
공식 코드RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via Multi-Prototype Learning
https://github.com/Kaylee0501/ImplexConv
공식 코드https://github.com/KeremTurgutlu/clip_art
공식 코드CLIP-Art: Contrastive Pre-training for Fine-Grained Art Classification
https://github.com/KeremTurgutlu/self_supervised
공식 코드CLIP-Art: Contrastive Pre-training for Fine-Grained Art Classification
https://github.com/Kevinnest/MSJE
공식 코드Learning TFIDF Enhanced Joint Embedding for Recipe-Image Cross-Modal Retrieval Service
https://github.com/KhrulkovV/hyperbolic-image-embeddings
공식 코드https://github.com/Kodezi/Chronos
공식 코드https://github.com/KoksiHub/Methods-For-SHREC-2021-Protein-Retrieval-and-Classification-Datasets
공식 코드https://github.com/KunpengLi1994/VSRN
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.