Papers with Code 아카이브
Model Optimization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 0
- 보존된 평가 기록
- 0
To Optimize already existing models in Training/Inferencing tasks.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/KrishnaRJ422/Explainability_Bias_Fairness-in-AI
https://github.com/MatthiasNickles/diff-SAT
https://github.com/PaddlePaddle/PaddleOCR
Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion
https://github.com/Ruhallah93/superior-scoring-rules
Superior Scoring Rules for Probabilistic Evaluation of Single-Label Multi-Class Classification Tasks
https://github.com/TsingZ0/PFL-Non-IID
https://github.com/abhaskumarsinha/GRU-varients
https://github.com/awslabs/autogluon
https://github.com/bahmanmdd/HDLMF_GIN-GA
A hybrid deep-learning-metaheuristic framework for bi-level network design problems
https://github.com/bcmi220/unisrl
Dependency or Span, End-to-End Uniform Semantic Role Labeling
https://github.com/beyondguo/TrainingDynamics
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
https://github.com/bradyfu/awesome-multimodal-large-language-models
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
https://github.com/ctrlovefly/df4lcz
SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints
https://github.com/dk-liang/AutoScale_regression
AutoScale: Learning to Scale for Crowd Counting and Localization
https://github.com/dual-grp/pFedMe
https://github.com/dyahadila/ood_cartography
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
https://github.com/eliorc/tavolo
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
https://github.com/fudandisc/reform-eval
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
https://github.com/jia-hao999/samba
VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning
https://github.com/kakaobrain/honeybee
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
https://github.com/mileyan/pseudo-LiDAR_e2e
https://github.com/mindspore-lab/mindocr
Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion
https://github.com/npuliyang/Personality-Detection-MTL
https://github.com/open-mmlab/mmocr
Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion
https://github.com/opendatalab/PDF-Extract-Kit
https://github.com/reso1/ls-mcpp
https://github.com/szhang42/uneven_training_data
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
https://github.com/tanmaypandey7/wheat-detection
https://github.com/thejungwon/gc-fed
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning
https://github.com/urbanarchitect/urbanarchitect
Urban Architect: Steerable 3D Urban Scene Generation with Layout Prior
https://github.com/xxlya/Fed_ABIDE
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.