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Datasets/AM

AM

Benchmarks

Node Classification/Accuracy

Related Benchmarks

AM-2K/Image Matting/MADAM-2K/Image Matting/MSEAM-2K/Image Matting/SADAMASS/1 Image, 2*2 Stitchi/ADEAMASS/1 Image, 2*2 Stitchi/APDAMASS/1 Image, 2*2 Stitchi/APDEAMASS/1 Image, 2*2 Stitchi/Average MPJPE (mm) 1000 msecAMASS/1 Image, 2*2 Stitchi/FDEAMASS/1 Image, 2*2 Stitchi/FDE@1000ms (mm)AMASS/1 Image, 2*2 Stitchi/FDE@560ms (mm)AMASS/1 Image, 2*2 Stitchi/FDE@720ms (mm)AMASS/1 Image, 2*2 Stitchi/FDE@880ms (mm)AMASS/3D/ADEAMASS/3D/APDAMASS/3D/APDEAMASS/3D/Average MPJPE (mm) 1000 msecAMASS/3D/FDEAMASS/3D/FDE@1000ms (mm)AMASS/3D/FDE@560ms (mm)AMASS/3D/FDE@720ms (mm)AMASS/3D/FDE@880ms (mm)AMASS/Pose Estimation/ADEAMASS/Pose Estimation/APDAMASS/Pose Estimation/APDEAMASS/Pose Estimation/Average MPJPE (mm) 1000 msecAMASS/Pose Estimation/FDEAMASS/Pose Estimation/FDE@1000ms (mm)AMASS/Pose Estimation/FDE@560ms (mm)AMASS/Pose Estimation/FDE@720ms (mm)AMASS/Pose Estimation/FDE@880ms (mm)AMBER/Visual Question Answering/AccuracyAMBER/Visual Question Answering/F1AMBER/Visual Question Answering (VQA)/AccuracyAMBER/Visual Question Answering (VQA)/F1AMC23/Mathematical Reasoning/AccAMD/Image Matting/MADAMD/Image Matting/MSEAMI/Speaker Diarization/DER(%)AMI/Speaker Diarization/FAAMI/Speaker Diarization/MissAMI/Text Summarization/ROUGE-1AMI/Text Summarization/ROUGE-2AMI/Text Summarization/ROUGE-LAMI IMH/Speech Recognition/Word Error Rate (WER)AMI Lapel/Speaker Diarization/DER(%)AMI Meeting Corpus/Meeting Summarization/ROUGE-1 F1AMI MixHeadset/Speaker Diarization/DER(%)AMI SDM1/Speech Recognition/Word Error Rate (WER)AMIGOS/Continuous Affect Estimation/CCC (Arousal)AMIGOS/Continuous Affect Estimation/CCC (Valence)AMIGOS/Continuous Affect Estimation/PCC (Arousal)AMIGOS/Continuous Affect Estimation/PCC (Valence)AMOS/Medical Image Segmentation/Average DiceAMPLUS/Node Classification/AccuracyAMR (chinese, MRP 2020)/Semantic Parsing/F1AMR (english, MRP 2020)/Semantic Parsing/F1AMR3.0/Data-to-Text Generation/BleuAMR3.0/Text Generation/BleuAMZ Comp/Node Classification/AccuracyAMZ Computers/Node Classification/AccuracyAMZ Computers: fixed 20 node per class/Node Classification/AccuracyAMZ Photo/Node Classification/AccuracyAMiner/Node Property Prediction/normalized MSEAmazon/Classification/AccuracyAmazon/Click-Through Rate Prediction/AUCAmazon/Community Detection/Accuracy-NEAmazon/Community Detection/F1-scoreAmazon/Community Detection/NMIAmazon/Document Classification/AccuracyAmazon/Information Retrieval/HR@30Amazon/Link Prediction/F1-ScoreAmazon/Link Prediction/PR AUCAmazon/Link Prediction/ROC AUCAmazon/Text Classification/AccuracyAmazon/Text Summarization/ROUGE-1Amazon/Text Summarization/ROUGE-2Amazon/Text Summarization/ROUGE-LAmazon Baby/Recommendation Systems/Hit RatioAmazon Baby/Recommendation Systems/NDCG@20Amazon Baby/Recommendation Systems/RecallAmazon Baby/Recommendation Systems/nDCGAmazon Beauty/Recommendation Systems/HR@10Amazon Beauty/Recommendation Systems/Hit RatioAmazon Beauty/Recommendation Systems/Hit@10Amazon Beauty/Recommendation Systems/NDCGAmazon Beauty/Recommendation Systems/NDCG@10Amazon Beauty/Recommendation Systems/RecallAmazon Beauty/Recommendation Systems/nDCGAmazon Beauty/Recommendation Systems/nDCG@10Amazon Books/Recommendation Systems/Recall@20Amazon C&A/Recommendation Systems/Hits@10Amazon C&A/Recommendation Systems/Hits@20Amazon C&A/Recommendation Systems/nDCG@10Amazon C&A/Recommendation Systems/nDCG@20Amazon Cell Phones/Recommendation Systems/Hit@5Amazon Clothing/Recommendation Systems/NDCG@20Amazon Computers/Node Classification/AccuracyAmazon Counterfeit/Classification/AccuracyAmazon Counterfeit/Few-Shot Text Classification/AccuracyAmazon Counterfeit/Text Classification/AccuracyAmazon Dataset/Click-Through Rate Prediction/AUCAmazon Digital Music/Recommendation Systems/Hit RatioAmazon Digital Music/Recommendation Systems/RecallAmazon Digital Music/Recommendation Systems/nDCGAmazon Fashion/Recommendation Systems/AUCAmazon Fashion/Recommendation Systems/Hit@10Amazon Fashion/Recommendation Systems/HitRatio@ 10 (100 Neg. Samples)Amazon Fashion/Recommendation Systems/NDCGAmazon Fashion/Recommendation Systems/nDCG@10 (100 Neg. Samples)Amazon Fashion/Recommendation Systems/nDCG@10 (500 Neg. Samples)Amazon Games/Recommendation Systems/AUCAmazon Games/Recommendation Systems/Hit@10Amazon Games/Recommendation Systems/NDCGAmazon Games/Recommendation Systems/nDCG@10Amazon MTPP/Point Processes/Accuracy (%)Amazon MTPP/Point Processes/MAEAmazon MTPP/Point Processes/OTDAmazon MTPP/Point Processes/T-mAPAmazon Men/Recommendation Systems/Hit@10Amazon Men/Recommendation Systems/NDCGAmazon Men/Recommendation Systems/nDCG@10Amazon Office Products/Recommendation Systems/Hit RatioAmazon Office Products/Recommendation Systems/RecallAmazon Office Products/Recommendation Systems/nDCGAmazon Photo/Node Classification/AccuracyAmazon Product Data/Recommendation Systems/AUCAmazon Product Data/Recommendation Systems/F1Amazon Review Full/Sentiment Analysis/AccuracyAmazon Review Polarity/Sentiment Analysis/AccuracyAmazon Sports/Recommendation Systems/NGCG@20Amazon Toys & Games/Recommendation Systems/Hit RatioAmazon Toys & Games/Recommendation Systems/RecallAmazon Toys & Games/Recommendation Systems/nDCGAmazon-12K/Classification/P@1Amazon-12K/Classification/P@3Amazon-12K/Classification/P@5Amazon-12K/Classification/nDCG@3Amazon-12K/Classification/nDCG@5Amazon-12K/Multi-Label Text Classification/P@1Amazon-12K/Multi-Label Text Classification/P@3Amazon-12K/Multi-Label Text Classification/P@5Amazon-12K/Multi-Label Text Classification/nDCG@3Amazon-12K/Multi-Label Text Classification/nDCG@5Amazon-12K/Text Classification/P@1Amazon-12K/Text Classification/P@3Amazon-12K/Text Classification/P@5Amazon-12K/Text Classification/nDCG@3Amazon-12K/Text Classification/nDCG@5Amazon-2/Classification/ErrorAmazon-2/Text Classification/ErrorAmazon-5/Chatbot/1 in 10 R@2Amazon-5/Classification/ErrorAmazon-5/Dialogue/1 in 10 R@2Amazon-5/Dialogue Generation/1 in 10 R@2Amazon-5/Text Classification/ErrorAmazon-5/Text Generation/1 in 10 R@2Amazon-Beauty/Recommendation Systems/HR@10Amazon-Beauty/Recommendation Systems/HR@20Amazon-Beauty/Recommendation Systems/HR@5Amazon-Beauty/Recommendation Systems/HR@50Amazon-Beauty/Recommendation Systems/MAP@20Amazon-Beauty/Recommendation Systems/MRR@10Amazon-Beauty/Recommendation Systems/MRR@20Amazon-Beauty/Recommendation Systems/MRR@50Amazon-Beauty/Recommendation Systems/NDCG@20Amazon-Beauty/Recommendation Systems/NDCG@5Amazon-Beauty/Recommendation Systems/NDCG@50Amazon-Beauty/Recommendation Systems/nDCG@10Amazon-Book/Collaborative Filtering/NDCG@20Amazon-Book/Collaborative Filtering/Recall@20Amazon-Book/Recommendation Systems/HR@10Amazon-Book/Recommendation Systems/HR@50Amazon-Book/Recommendation Systems/NDCG@10Amazon-Book/Recommendation Systems/NDCG@50Amazon-Book/Recommendation Systems/Recall@20Amazon-Book/Recommendation Systems/nDCG@20Amazon-CDs/Recommendation Systems/MAP@20Amazon-CDs/Recommendation Systems/MRR@20Amazon-CDs/Recommendation Systems/NDCG@20Amazon-CDs/Recommendation Systems/Recall@10Amazon-CDs/Recommendation Systems/nDCG@10Amazon-Electronics/Recommendation Systems/MAP@20Amazon-Electronics/Recommendation Systems/MRR@20Amazon-Electronics/Recommendation Systems/NDCG@20Amazon-Fraud/Active Speaker Detection/AUC-ROCAmazon-Fraud/Active Speaker Detection/Averaged PrecisionAmazon-Fraud/Active Speaker Detection/F1 MacroAmazon-Fraud/Active Speaker Detection/G-meanAmazon-Fraud/Anomaly Detection/AUCAmazon-Fraud/Fraud Detection/AUC-ROCAmazon-Fraud/Fraud Detection/Averaged PrecisionAmazon-Fraud/Fraud Detection/F1 MacroAmazon-Fraud/Fraud Detection/G-meanAmazon-Fraud/Node Classification/AUC-ROCAmazon-Google/Data Integration/Candidate Set SizeAmazon-Google/Data Integration/F1 (%)Amazon-Google/Data Integration/RecallAmazon-Google/Entity Resolution/Candidate Set SizeAmazon-Google/Entity Resolution/F1 (%)Amazon-Google/Entity Resolution/RecallAmazon-Health/Recommendation Systems/MAP@20Amazon-Health/Recommendation Systems/MRR@20Amazon-Health/Recommendation Systems/NDCG@20Amazon-Movies/Recommendation Systems/MAP@20Amazon-Movies/Recommendation Systems/MRR@20Amazon-Movies/Recommendation Systems/NDCG@20Amazon-Sports/Recommendation Systems/HR@10Amazon-Sports/Recommendation Systems/HR@20Amazon-Sports/Recommendation Systems/HR@5Amazon-Sports/Recommendation Systems/MRR@10Amazon-Sports/Recommendation Systems/NDCG@10Amazon-Sports/Recommendation Systems/NDCG@5Amazon-Toys/Recommendation Systems/HR@5Amazon-Video-Games/Recommendation Systems/HR@10Amazon-Video-Games/Recommendation Systems/MRR@10Amazon-Video-Games/Recommendation Systems/NDCG@10Amazon-book/Recommendation Systems/Recall@20Amazon-employee-access/Core set discovery/F1(10-fold)Amazon2M/Node Classification/F1Ambiguious-HOI/Human-Object Interaction Detection/mAPAmsterTime/Image Classification/AccuracyAmsterTime/Image Retrieval/mAPAmsterTime/Visual Place Recognition/Recall@1AmsterTime/Visual Place Recognition/Recall@10AmsterTime/Visual Place Recognition/Recall@5amazon-ratings/Node Classification/Accuracy (%)

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Tasks

Node Classification