https://github.com/lucidrains/musiclm-pytorch
MuLan: A Joint Embedding of Music Audio and Natural Language
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
MuLan: A Joint Embedding of Music Audio and Natural Language
Let's Transfer Transformations of Shared Semantic Representations
Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval
Adversarial Autoencoders for Compact Representations of 3D Point Clouds
Extending Context Window of Large Language Models via Positional Interpolation
Vision-Language Models in Remote Sensing: Current Progress and Future Trends
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
NetVLAD: CNN architecture for weakly supervised place recognition
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Scaling up Trustless DNN Inference with Zero-Knowledge Proofs
Vision-Language Models in Remote Sensing: Current Progress and Future Trends
Circle Loss: A Unified Perspective of Pair Similarity Optimization
Condensed Movies: Story Based Retrieval with Contextual Embeddings
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval
HADA: A Graph-based Amalgamation Framework in Image-text Retrieval
code2seq: Generating Sequences from Structured Representations of Code
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction
A Critical Review of Recurrent Neural Networks for Sequence Learning
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
Building a Manga Dataset "Manga109" with Annotations for Multimedia Applications
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation Pipeline
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.