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@@ -104,33 +104,34 @@ permalink: /docs/lsc/leaderboards/
 |  6  |  **MolNet_Ensemble**  | Yes | 0.0753  | 0.0797 | polixir.ai | [zouxiaochuan](mailto:[email protected]) (polixir.ai) | [Paper](https://github.com/zouxiaochuan/code_ogblsc2022/blob/main/molnet2022_arxiv.pdf), [Code](https://github.com/zouxiaochuan/code_ogblsc2022) | 32,047,874 | 8 RTX3090 | Nov 1, 2022 |
 |  7  |  **Global-ViSNet**  | No | 0.0766  | 0.0784 | ViSNet | [Tong Wang](mailto:[email protected]) (Microsoft Research AI4Science) | [Paper](https://github.com/ogb-visnet/Global-ViSNet/blob/master/ViSNet_Tech_Report.pdf), [Code](https://github.com/ogb-visnet/Global-ViSNet) | 78,450,692 | 4 NVIDIA A100 GPUs | Oct 26, 2022 |
 |  8  |  **Transformer-M**  | No | 0.0782  | 0.0772 | FML Lab@PKU | [Shengjie Luo](mailto:[email protected]) (Peking University) | [Paper](https://arxiv.org/abs/2210.01765), [Code](https://github.com/lsj2408/Transformer-M) | 68,957,249 | 4 NVIDIA Tesla A100 GPUs (40GB) | Oct 5, 2022 |
-|  9  |  **GEM-2**  | No | 0.0806  | 0.0793 | PaddleHelix | [Donglong He](mailto:[email protected]) (Baidu) | [Paper](https://arxiv.org/abs/2208.05863), [Code](https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/pretrained_compound/ChemRL/GEM-2) | 32,086,707 | 16 NVIDIA A100 | Aug 11, 2022 |
-|  10  |  **GPTrans-L**  | No | 0.0821  | 0.0809 | IMAGINE@NJU | [Zhe Chen](mailto:[email protected]) (Nanjing University) | [Paper](https://arxiv.org/abs/2305.11424), [Code](https://github.com/czczup/GPTrans/tree/main) | 85,995,713 | 8 NVIDIA A100 GPUs | Jun 6, 2023 |
-|  11  |  **GPTrans-T**  | No | 0.0842  | 0.0833 | IMAGINE@NJU | [Zhe Chen](mailto:[email protected]) (Nanjing University) | [Paper](https://arxiv.org/abs/2305.11424), [Code](https://github.com/czczup/GPTrans/tree/main) | 6,577,697 | 8 NVIDIA A100 GPUs | Jun 14, 2023 |
-|  12  |  **Deep graph transformer**  | Yes | 0.0843  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 26, 2022 |
-|  13  |  **Deep graph transformer**  | Yes | 0.0844  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 19, 2022 |
-|  14  |  **Deep graph transformer**  | Yes | 0.0852  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 11, 2022 |
-|  15  |  **GraphGPT(MLM pretrained)**  | No | 0.0856  | 0.0847 | Alibaba-DT | [Qifang Zhao](mailto:[email protected]) (Alibaba) | [Paper](https://arxiv.org/abs/2401.00529), [Code](https://github.com/alibaba/graph-gpt) | 453,388,801 | 4 Nvidia L40S | Aug 11, 2024 |
-|  16  |  **EGT**  | No | 0.0862  | 0.0857 | EFT-AIRC | [Md Shamim Hussain](mailto:[email protected]) (RPI / IBM) | [Paper](https://arxiv.org/abs/2108.03348), [Code](https://github.com/shamim-hussain/egt_pytorch) | 89,326,465 | 8 Tesla V100 (32GB) | Jun 24, 2022 |
-|  16  |  **GPS**  | No | 0.0862  | 0.0852 | Mila | [Ladislav Rampasek](mailto:[email protected]) (Mila / Universite de Montreal) | [Paper](https://arxiv.org/abs/2205.12454), [Code](https://github.com/rampasek/GraphGPS) | 13,807,345 | 1 NVIDIA A100 (40GB) | Nov 10, 2022 |
-|  17  |  **CoAtGIN-base**  | No | 0.0866  | 0.0859 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 9,938,433 | 8 NVIDIA A40 | Sep 30, 2022 |
-|  18  |  **EGT+LSPE+HIERA_clustering**  | No | 0.0868  | 0.0863 | rwlspegate2 | [YEOM JE YOON](mailto:[email protected]) (University of Seoul) | [Paper](https://github.com/emforce77/rwlspegate2/blob/c3b83ac0a1f0d1dc67e3f59d928eb092dd797cd4/technical_report.pdf), [Code](https://github.com/emforce77/rwlspegate2.git) | 90,102,913 | NVIDIA A100 80GB HBM2E SXM4 | Feb 16, 2023 |
-|  19  |  **EGT**  | No | 0.0872  | 0.0869 | EGT-AIRC | [Md Shamim Hussain](mailto:[email protected]) (RPI / IBM) | [Paper](https://arxiv.org/abs/2108.03348), [Code](https://github.com/shamim-hussain/egt_pytorch) | 89,326,465 | 8 Tesla V100 (32GB) | Jan 26, 2022 |
-|  20  |  **GRPE-Large**  | No | 0.0876  | 0.0867 | WonWoo | [Wonpyo Park](mailto:[email protected]) (SNU / Standigm) | [Paper](https://arxiv.org/abs/2201.12787), [Code](https://github.com/lenscloth/GRPE) | 118,300,000 | 8 A100-SXM4-40GB | Aug 14, 2022 |
-|  21  |  **GraphSelfAttention**  | No | 0.0898  | 0.0890 | WonWoo | [Wonpyo Park](mailto:[email protected]) (Standigm) | [Paper](https://arxiv.org/abs/2201.12787), [Code](https://github.com/lenscloth/GraphSelfAttention) | 46,199,041 | 4 A100 GPU | Nov 15, 2021 |
-|  22  |  **Deep graph transformer**  | Yes | 0.0904  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 3, 2022 |
-|  23  |  **CoAtGIN-tiny**  | No | 0.0908  | 0.0901 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 6,395,393 | 1 NVIDIA A40 | Sep 20, 2022 |
-|  24  |  **TokenGT (Lap)**  | No | 0.0919  | 0.0910 | vl-kaist | [Jinwoo Kim](mailto:[email protected]) (KAIST) | [Paper](https://arxiv.org/abs/2207.02505), [Code](https://github.com/jw9730/tokengt) | 48,492,289 | NVIDIA RTX 3090 x 8 | Aug 8, 2022 |
-|  25  |  **CoAtGIN-tiny**  | No | 0.0921  | 0.0916 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 6,183,425 | 1 NVIDIA A40 | Sep 8, 2022 |
-|  26  |  **CoAtGIN-tiny**  | No | 0.0935  | 0.0933 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 5,460,225 | NVIDIA A40 | Aug 29, 2022 |
-|  27  |  **HFAGNN**  | No | 0.1010  | 0.1005 | Zhuque Zhejianglab | [Can Xu](mailto:[email protected]) (Zhejiang Lab) | [Paper](https://github.com/Tigerrr07/HFAGNN/blob/master/technical_report.pdf), [Code](https://github.com/Tigerrr07/HFAGNN) | 3,949,959 | 1 NVIDIA TITAN V GPU(12GB memory) | Oct 30, 2022 |
-|  28  |  **GIN-virtual**  | No | 0.1084  | 0.1083 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 6,656,406 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
-|  29  |  **GCN-virtual**  | No | 0.1152  | 0.1153 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 4,850,401 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
-|  30  |  **GIN**  | No | 0.1218  | 0.1195 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 3,761,406 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
-|  31  |  **GraphGPS without PE (subset)**  | No | 0.1395  | 0.1334 | GraphLARS | [Xu Wang](mailto:[email protected]) (4Paradigm && EE Tsinghua) | [Paper](https://arxiv.org/abs/2205.12454), [Code](https://github.com/rampasek/GraphGPS) | 6,155,089 | 1 RTX3090 (24GB GPU) | Sep 2, 2022 |
-|  32  |  **GCN**  | No | 0.1398  | 0.1379 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 1,955,401 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
-|  33  |  **MLP-Fingerprint**  | No | 0.1760  | 0.1753 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 16,107,201 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
-|  34  |  **MolNet_Ensemble**  | Yes | 0.9899  | 0.0847 | polixir.ai | [xiaochuan zou](mailto:[email protected]) (polixir.ai) | [Paper](https://github.com/zouxiaochuan/code_ogblsc2022/blob/main/molnet2022_arxiv.pdf), [Code](https://github.com/zouxiaochuan/code_ogblsc2022) | 32,047,874 | 8 RTX3090 | Oct 24, 2022 |
+|  9  |  **GraphGPT(MLM tv10k)**  | No | 0.0804  | 0.0840 | Alibaba-DT | [Qifang Zhao](mailto:[email protected]) (Alibaba) | [Paper](https://arxiv.org/abs/2401.00529), [Code](https://github.com/alibaba/graph-gpt) | 453,388,801 | 4 Nvidia L40S | Aug 21, 2024 |
+|  10  |  **GEM-2**  | No | 0.0806  | 0.0793 | PaddleHelix | [Donglong He](mailto:[email protected]) (Baidu) | [Paper](https://arxiv.org/abs/2208.05863), [Code](https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/pretrained_compound/ChemRL/GEM-2) | 32,086,707 | 16 NVIDIA A100 | Aug 11, 2022 |
+|  11  |  **GPTrans-L**  | No | 0.0821  | 0.0809 | IMAGINE@NJU | [Zhe Chen](mailto:[email protected]) (Nanjing University) | [Paper](https://arxiv.org/abs/2305.11424), [Code](https://github.com/czczup/GPTrans/tree/main) | 85,995,713 | 8 NVIDIA A100 GPUs | Jun 6, 2023 |
+|  12  |  **GPTrans-T**  | No | 0.0842  | 0.0833 | IMAGINE@NJU | [Zhe Chen](mailto:[email protected]) (Nanjing University) | [Paper](https://arxiv.org/abs/2305.11424), [Code](https://github.com/czczup/GPTrans/tree/main) | 6,577,697 | 8 NVIDIA A100 GPUs | Jun 14, 2023 |
+|  13  |  **Deep graph transformer**  | Yes | 0.0843  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 26, 2022 |
+|  14  |  **Deep graph transformer**  | Yes | 0.0844  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 19, 2022 |
+|  15  |  **Deep graph transformer**  | Yes | 0.0852  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 11, 2022 |
+|  16  |  **GraphGPT(MLM pretrained)**  | No | 0.0856  | 0.0847 | Alibaba-DT | [Qifang Zhao](mailto:[email protected]) (Alibaba) | [Paper](https://arxiv.org/abs/2401.00529), [Code](https://github.com/alibaba/graph-gpt) | 453,388,801 | 4 Nvidia L40S | Aug 11, 2024 |
+|  17  |  **EGT**  | No | 0.0862  | 0.0857 | EFT-AIRC | [Md Shamim Hussain](mailto:[email protected]) (RPI / IBM) | [Paper](https://arxiv.org/abs/2108.03348), [Code](https://github.com/shamim-hussain/egt_pytorch) | 89,326,465 | 8 Tesla V100 (32GB) | Jun 24, 2022 |
+|  17  |  **GPS**  | No | 0.0862  | 0.0852 | Mila | [Ladislav Rampasek](mailto:[email protected]) (Mila / Universite de Montreal) | [Paper](https://arxiv.org/abs/2205.12454), [Code](https://github.com/rampasek/GraphGPS) | 13,807,345 | 1 NVIDIA A100 (40GB) | Nov 10, 2022 |
+|  18  |  **CoAtGIN-base**  | No | 0.0866  | 0.0859 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 9,938,433 | 8 NVIDIA A40 | Sep 30, 2022 |
+|  19  |  **EGT+LSPE+HIERA_clustering**  | No | 0.0868  | 0.0863 | rwlspegate2 | [YEOM JE YOON](mailto:[email protected]) (University of Seoul) | [Paper](https://github.com/emforce77/rwlspegate2/blob/c3b83ac0a1f0d1dc67e3f59d928eb092dd797cd4/technical_report.pdf), [Code](https://github.com/emforce77/rwlspegate2.git) | 90,102,913 | NVIDIA A100 80GB HBM2E SXM4 | Feb 16, 2023 |
+|  20  |  **EGT**  | No | 0.0872  | 0.0869 | EGT-AIRC | [Md Shamim Hussain](mailto:[email protected]) (RPI / IBM) | [Paper](https://arxiv.org/abs/2108.03348), [Code](https://github.com/shamim-hussain/egt_pytorch) | 89,326,465 | 8 Tesla V100 (32GB) | Jan 26, 2022 |
+|  21  |  **GRPE-Large**  | No | 0.0876  | 0.0867 | WonWoo | [Wonpyo Park](mailto:[email protected]) (SNU / Standigm) | [Paper](https://arxiv.org/abs/2201.12787), [Code](https://github.com/lenscloth/GRPE) | 118,300,000 | 8 A100-SXM4-40GB | Aug 14, 2022 |
+|  22  |  **GraphSelfAttention**  | No | 0.0898  | 0.0890 | WonWoo | [Wonpyo Park](mailto:[email protected]) (Standigm) | [Paper](https://arxiv.org/abs/2201.12787), [Code](https://github.com/lenscloth/GraphSelfAttention) | 46,199,041 | 4 A100 GPU | Nov 15, 2021 |
+|  23  |  **Deep graph transformer**  | Yes | 0.0904  | 0.0891 | NVIDIA-PCQM4Mv2 | [Jiwei Liu](mailto:[email protected]) (NVIDIA) | [Paper](https://github.com/daxiongshu/PCQM4Mv2_subs/blob/main/tech_report.pdf), [Code](https://github.com/daxiongshu/PCQM4Mv2_subs) | 63,600,000 | 1 NVIDIA V100 GPU 32 GB | Oct 3, 2022 |
+|  24  |  **CoAtGIN-tiny**  | No | 0.0908  | 0.0901 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 6,395,393 | 1 NVIDIA A40 | Sep 20, 2022 |
+|  25  |  **TokenGT (Lap)**  | No | 0.0919  | 0.0910 | vl-kaist | [Jinwoo Kim](mailto:[email protected]) (KAIST) | [Paper](https://arxiv.org/abs/2207.02505), [Code](https://github.com/jw9730/tokengt) | 48,492,289 | NVIDIA RTX 3090 x 8 | Aug 8, 2022 |
+|  26  |  **CoAtGIN-tiny**  | No | 0.0921  | 0.0916 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 6,183,425 | 1 NVIDIA A40 | Sep 8, 2022 |
+|  27  |  **CoAtGIN-tiny**  | No | 0.0935  | 0.0933 | xfcui@sdu | [Xuefeng Cui](mailto:[email protected]) (Shandong University) | [Paper](https://www.biorxiv.org/content/10.1101/2022.08.26.505499v1), [Code](https://github.com/xfcui/CoAtGIN) | 5,460,225 | NVIDIA A40 | Aug 29, 2022 |
+|  28  |  **HFAGNN**  | No | 0.1010  | 0.1005 | Zhuque Zhejianglab | [Can Xu](mailto:[email protected]) (Zhejiang Lab) | [Paper](https://github.com/Tigerrr07/HFAGNN/blob/master/technical_report.pdf), [Code](https://github.com/Tigerrr07/HFAGNN) | 3,949,959 | 1 NVIDIA TITAN V GPU(12GB memory) | Oct 30, 2022 |
+|  29  |  **GIN-virtual**  | No | 0.1084  | 0.1083 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 6,656,406 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
+|  30  |  **GCN-virtual**  | No | 0.1152  | 0.1153 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 4,850,401 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
+|  31  |  **GIN**  | No | 0.1218  | 0.1195 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 3,761,406 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
+|  32  |  **GraphGPS without PE (subset)**  | No | 0.1395  | 0.1334 | GraphLARS | [Xu Wang](mailto:[email protected]) (4Paradigm && EE Tsinghua) | [Paper](https://arxiv.org/abs/2205.12454), [Code](https://github.com/rampasek/GraphGPS) | 6,155,089 | 1 RTX3090 (24GB GPU) | Sep 2, 2022 |
+|  33  |  **GCN**  | No | 0.1398  | 0.1379 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 1,955,401 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
+|  34  |  **MLP-Fingerprint**  | No | 0.1760  | 0.1753 | OGB-LSC | [Weihua Hu](mailto:[email protected]) (Stanford) | [Paper](https://openreview.net/pdf?id=qkcLxoC52kL), [Code](https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2) | 16,107,201 | 1 GeForce RTX 2080 (11GB GPU) | Sep 8, 2021 |
+|  35  |  **MolNet_Ensemble**  | Yes | 0.9899  | 0.0847 | polixir.ai | [xiaochuan zou](mailto:[email protected]) (polixir.ai) | [Paper](https://github.com/zouxiaochuan/code_ogblsc2022/blob/main/molnet2022_arxiv.pdf), [Code](https://github.com/zouxiaochuan/code_ogblsc2022) | 32,047,874 | 8 RTX3090 | Oct 24, 2022 |
 
 
 
diff --git a/test-dev_master.csv b/test-dev_master.csv
@@ -82,4 +82,4 @@ time,unique_identifier,dataset,method,ensemble,approved,test_performance,val_per
 11/16/2023,65565301854b3,PCQM4Mv2,EGT+Tri. Attn.+RDKit Coords.,No,Yes,0.068258088757189,0.0671,EGT-AIRC,RPI / IBM,Md Shamim Hussain,[email protected],[email protected],1.3.5,https://github.com/shamim-hussain/egt_triangular,https://github.com/shamim-hussain/egt_triangular/blob/master/Report.pdf,203945093.0,"lr: [0.001, 0.002*], num_layers: [12,18,24*], hidden_channels: [512, 768*], source_dropout: [0.1,0.2, 0.3*], path_dropout: [0.1, 0.2*]",32 NVIDIA V100 (32 GB),8 Intel Xeon Gold 6248 CPU (3072 GB Memory),36 hours,1 hour
 11/23/2023,656035b4348b6,PCQM4Mv2,EGT+Tri. Attn. (Pure Neural),No,Yes,0.0698127663234968,0.0686,EGT-AIRC,RPI / IBM,Md Shamim Hussain,[email protected],[email protected],1.3.5,https://github.com/shamim-hussain/egt_triangular,https://github.com/shamim-hussain/egt_triangular/blob/master/Report.pdf,203894787.0,"lr: [0.001, 0.002*], num_layers: [12,18,24*], hidden_channels: [512, 768*], source_dropout: [0.1,0.2, 0.3*], path_dropout: [0.1, 0.2*]",32 NVIDIA V100 (32 GB),8 Intel Xeon Gold 6248 CPU (3072 GB Memory),36 hours,1 hour
 08/11/2024,66b994a9585c7,PCQM4Mv2,GraphGPT(MLM pretrained),No,Yes,0.0856246531063338,0.0847,Alibaba-DT,Alibaba,Qifang Zhao,[email protected],[email protected],1.3.6,https://github.com/alibaba/graph-gpt,https://arxiv.org/abs/2401.00529,453388801.0,"lr: [0.0001*, 0.0003], num_layers: [12,24,48*], hidden_channels: [512,768*], dropout: [0*, 0.1], path-dropout: [0, 0.1, 0.2*], epochs: [16,32*,40]",4 Nvidia L40S,1 Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz,30 hours,30 mins
-2024/08/21,66c6b8fa3a6e2,PCQM4Mv2,GraphGPT(MLM tv10k),No,Yes,0.0803508622332648,0.084,Alibaba-DT,Alibaba,Qifang Zhao,[email protected],[email protected],1.3.6,https://github.com/alibaba/graph-gpt,https://arxiv.org/abs/2401.00529,453388801.0,"lr: [0.0001*, 0.0003], num_layers: [12,24,48*], hidden_channels: [512,768*], dropout: [0*, 0.1], path-dropout: [0, 0.1, 0.2*], epochs: [16,32*,40], mask: [0.8,0,0.2]",4 Nvidia L40S,1 Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz,30 hours,30 mins
+08/21/2024,66c6b8fa3a6e2,PCQM4Mv2,GraphGPT(MLM tv10k),No,Yes,0.0803508622332648,0.084,Alibaba-DT,Alibaba,Qifang Zhao,[email protected],[email protected],1.3.6,https://github.com/alibaba/graph-gpt,https://arxiv.org/abs/2401.00529,453388801.0,"lr: [0.0001*, 0.0003], num_layers: [12,24,48*], hidden_channels: [512,768*], dropout: [0*, 0.1], path-dropout: [0, 0.1, 0.2*], epochs: [16,32*,40], mask: [0.8,0,0.2]",4 Nvidia L40S,1 Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz,30 hours,30 mins