Papers with Code 아카이브
Retrieval
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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/MarkWuNLP/ResponseEdit
공식 코드https://github.com/MarkWuNLP/TACNTN
공식 코드Response Selection with Topic Clues for Retrieval-based Chatbots
https://github.com/Marsrocky/GaitFi
공식 코드GaitFi: Robust Device-Free Human Identification via WiFi and Vision Multimodal Learning
https://github.com/MartinBoeckling/KGRag
공식 코드https://github.com/MasterBin-IIAU/UNINEXT
공식 코드Universal Instance Perception as Object Discovery and Retrieval
https://github.com/McGill-NLP/MLQuestions
공식 코드https://github.com/McGill-NLP/feedbackqa
공식 코드https://github.com/McGill-NLP/statcan-dialogue-dataset
공식 코드The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intents
https://github.com/MeiqiGuo/COLING2020-BiasStudy
공식 코드https://github.com/Microsoft/O-CNN
공식 코드O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
https://github.com/MiuLab/E2EMathSolver
공식 코드Semantically-Aligned Equation Generation for Solving and Reasoning Math Word Problems
https://github.com/MiuLab/KB-InfoBot
공식 코드Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access
https://github.com/MiuLab/RAG-Self-Preference
공식 코드LLMs are Biased Evaluators But Not Biased for Retrieval Augmented Generation
https://github.com/MiuLab/VisualDialog
공식 코드https://github.com/Monoxide-Chen/uncertainty_retrieval
공식 코드Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization
https://github.com/MooreThreads/TurboRAG
공식 코드TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text
https://github.com/Motion-RAG/MoRAG
공식 코드MoRAG -- Multi-Fusion Retrieval Augmented Generation for Human Motion
https://github.com/MrRezaeiUofT/AT-RAG
공식 코드https://github.com/MrZihan/NavRAG
공식 코드NavRAG: Generating User Demand Instructions for Embodied Navigation through Retrieval-Augmented LLM
https://github.com/MrZilinXiao/LongContextReranker
공식 코드LOCORE: Image Re-ranking with Long-Context Sequence Modeling
https://github.com/MubarizZaffar/VPR-Bench
공식 코드https://github.com/Music-and-Culture-Technology-Lab/omnizart
공식 코드Omnizart: A General Toolbox for Automatic Music Transcription
https://github.com/MyrtoLimnios/grad_2sample
공식 코드Concentration Inequalities for Two-Sample Rank Processes with Application to Bipartite Ranking
https://github.com/NEUIR/CONAN
공식 코드Building A Coding Assistant via the Retrieval-Augmented Language Model
https://github.com/NJUNLP/Knowledge-Free-Reasoning
공식 코드Large Language Models Are Cross-Lingual Knowledge-Free Reasoners
https://github.com/NLPJCL/RAG-Retrieval
공식 코드https://github.com/NTMC-Community/MatchZoo
공식 코드https://github.com/NTMC-Community/MatchZoo-Studio
공식 코드MatchZoo: A Learning, Practicing, and Developing System for Neural Text Matching
https://github.com/NVIDIA/Megatron-LM
공식 코드End-to-End Training of Neural Retrievers for Open-Domain Question Answering
https://github.com/NVIDIA/NeMo
공식 코드https://github.com/NVIDIA/audio-flamingo
공식 코드Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
https://github.com/NVlabs/GatedDeltaNet
공식 코드https://github.com/NVlabs/RelViT
공식 코드RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning
https://github.com/Natooz/music-modeling-time-duration
공식 코드Impact of time and note duration tokenizations on deep learning symbolic music modeling
https://github.com/NeosKnight233/MuDAF
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.