Aspect-based Sentiment Analysis on Laptop dataset benchmark leaderboard · SOTA2 Research

Aspect-based Sentiment Analysis on Laptop dataset

86.08AccuracyGHI

Evaluation Results

Method	Links
GHI2026.05		86.08	83.74
SARL2026.05		85.42	82.97
AGCL2026.05		84.54	82.15
PWCN2026.05		84.01	81.08
PConv2026.05		83.54	80.89
DAGF2026.05		83.07	80.38
RCL2026.05		82.76	80.28
DAGCN2026.05		82.59	79.4
S2GSL2026.05		82.46	79.07
MLFM2026.05		82.12	79.06
KumaGCN2026.05		81.98	78.81
APARN2026.05		81.96	79.1
DualGCN2026.05		81.8	78.1
SDGCN-BERT2019.06		81.35	78.34
SDGCN-BERT2019.12		81.35	78.34
TextGT2026.05		81.33	78.71
dotGCN2026.05		81.03	78.1
SSEGCN2026.05		81.01	77.96
LCF-ATEPC-Fusion2019.12		80.97	77.86
TGCN2026.05		80.88	77.03
LCF-ATEPC-CDM2019.12		80.03	76.6
LCF-ATEPC-CDW2019.12		80.03	77.17
AEN-BERT2019.06		79.93	76.31
AEN-BERT2019.12		79.93	76.31
DGEDT2026.05		79.8	75.6
MWGCN2026.05		79.78	76.68
BERT-SPC2019.12		79.56	75.55
BERT-BASE2019.12		79.4	75.24
SK-GCN2026.05		79	75.57
R-GAT2026.05		78.21	74.07
BERT-PT2019.12		78.07	75.08
SDGCN-G2019.06		75.55	71.35
SDGCN-A2019.06		75.39	70.04
RAN2019.06		74.49	71.35
PBAN2019.06		74.12	—
SDGCN-G w/o p2019.06		73.67	68.7
AEN2019.06		73.51	69.04
SDGCN-A w/o p2019.06		73.2	68.54
TSN2019.06		73.1	—
IAN2019.06		72.1	—
MenNet2019.06		70.33	64.09
ATAE-LSTM2019.06		68.7	—
TD-LSTM2019.06		68.13	—