Papers with Code 아카이브
Retrieval
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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/thunlp/KernelGAT
https://github.com/tjddus9597/Beyond-Binary-Supervision-CVPR19
https://github.com/tjdevWorks/ConVIRT-Federated
Contrastive Learning of Medical Visual Representations from Paired Images and Text
https://github.com/tkipf/gae
https://github.com/togethercomputer/llama-2-7b-32k-instruct
https://github.com/toooooodo/rgcn-linkprediction
https://github.com/torchrwkv/flash-linear-attention
https://github.com/toshi-k/kaggle-bengaliai-handwritten-grapheme-classification
https://github.com/tosmaster/imagevision
SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval
https://github.com/towhee-io/towhee
LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval
https://github.com/towhee-io/towhee/tree/main/towhee/models/nnfp
Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning
https://github.com/trackinglaboratory/tracklab
Body Part-Based Representation Learning for Occluded Person Re-Identification
https://github.com/transducens/LASERtrain
Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
https://github.com/tuananh1007/CNN-Image-Retrieval-in-PyTorch
CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples
https://github.com/tzirakis/Multimodal-Emotion-Recognition
End-to-End Multimodal Emotion Recognition using Deep Neural Networks
https://github.com/ubc-vision/make-a-story
https://github.com/ucl-exoplanets/ADC2023-baseline
Peeking inside the Black Box: Interpreting Deep Learning Models for Exoplanet Atmospheric Retrievals
https://github.com/uclnlp/APE
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/uditsharma29/flynet-cann
A Hybrid Compact Neural Architecture for Visual Place Recognition
https://github.com/ukplab/acl2022-impli
Potential Idiomatic Expression (PIE)-English: Corpus for Classes of Idioms
https://github.com/ungeimer/Etiquetadorv1
Active learning in annotating micro-blogs dealing with e-reputation
https://github.com/ungeimer/FLAT-TextTagger
Active learning in annotating micro-blogs dealing with e-reputation
https://github.com/ungeimer/FLAT-lite
Active learning in annotating micro-blogs dealing with e-reputation
https://github.com/ungeimer/TextTagger-Docker
Active learning in annotating micro-blogs dealing with e-reputation
https://github.com/unicamp-dl/retailGPT
Retail-GPT: leveraging Retrieval Augmented Generation (RAG) for building E-commerce Chat Assistants
https://github.com/unitaryai/VTC
https://github.com/unsuthee/VariationalDeepSemanticHashing
https://github.com/uw-madison-lee-lab/icl-hcg
https://github.com/uzh-rpg/netvlad_tf_open
NetVLAD: CNN architecture for weakly supervised place recognition
https://github.com/uzh-rpg/ssms_event_cameras
https://github.com/vano1205/efficientcl
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations
https://github.com/vanzytay/WSDM2018_HyperQA
Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering
https://github.com/vearch/vearch
The Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform
https://github.com/vectara/FaithJudge
FaithBench: A Diverse Hallucination Benchmark for Summarization by Modern LLMs
https://github.com/vectara/hallucination-leaderboard
AlignScore: Evaluating Factual Consistency with a Unified Alignment Function
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.