https://github.com/ylqi/count-anything
Learning Transferable Visual Models From Natural Language Supervision
Papers with Code 아카이브
Data-free Knowledge Distillation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yolo0226/mmdetection-master
https://github.com/yongbowin/MSMARCO-Question-Answering_annotation
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
https://github.com/yongbowin/OpenKP_annotation
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
https://github.com/yoonkim/neural-qcfg
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
https://github.com/yorkerlin/remove-the-square-root
https://github.com/yossilevii100/critical_points2
Benchmarking and Analyzing Point Cloud Classification under Corruptions
https://github.com/yossilevii100/refocusing
Benchmarking and Analyzing Point Cloud Classification under Corruptions
https://github.com/youngwanLEE/rc-mae
Benchmarking Detection Transfer Learning with Vision Transformers
https://github.com/yshuqiao/cascade_rcnn_fabricDetection
https://github.com/yuchen814/codehalu
https://github.com/yueatsprograms/ttt_cifar_release
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
https://github.com/yueatsprograms/ttt_imagenet_release
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
https://github.com/yufanchen96/RoDLA
RoDLA: Benchmarking the Robustness of Document Layout Analysis Models
https://github.com/yukexing/3dgs-ieval-15k
LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMs
https://github.com/yuuun/clip_pytorch
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/yuyouyu32/beyonddialogue
RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models
https://github.com/ywjawmw/shennong-tcm-evaluation-benchmark
https://github.com/yzhao062/pyod
AD-LLM: Benchmarking Large Language Models for Anomaly Detection
https://github.com/yzhao062/yzhao062
https://github.com/zahrag/BIOSCAN-5M
An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders
https://github.com/zamnius/uNet-seg-decathlon
https://github.com/zengzhaoyang/mymmdet
https://github.com/zeroxleo/ml-agent
MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
https://github.com/zezhishao/d2stgnn
https://github.com/zezhishao/step
https://github.com/zhanggefan/mmdet-yolov4
https://github.com/zhanghanbo/invig-dataset
InViG: Benchmarking Interactive Visual Grounding with 500K Human-Robot Interactions
https://github.com/zhangxu0963/npc
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/zhaochenyang20/Prompt2Model-Self-Guide
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
https://github.com/zhaoyang97/mmdetection
https://github.com/zhongmicai/Methylation_notes
https://github.com/zhouhing/Mself_mmdetection
https://github.com/zhuang-group/lit
https://github.com/zhyings/cbm
https://github.com/zihanzhaosjtu/librisqa
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.