task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
Long-Context Understanding | Ada-LEval (TSort) | Vicuna-7b-v1.5-16k | https://arxiv.org/abs/2306.05685v4 | 8k | 2.3 |
Long-Context Understanding | Ada-LEval (TSort) | Vicuna-7b-v1.5-16k | https://arxiv.org/abs/2306.05685v4 | 16k | 1.7 |
Long-Context Understanding | Ada-LEval (TSort) | InternLM2-7b | https://arxiv.org/abs/2403.17297v1 | 2k | 5.1 |
Long-Context Understanding | Ada-LEval (TSort) | InternLM2-7b | https://arxiv.org/abs/2403.17297v1 | 4k | 3.9 |
Long-Context Understanding | Ada-LEval (TSort) | InternLM2-7b | https://arxiv.org/abs/2403.17297v1 | 8k | 5.1 |
Long-Context Understanding | Ada-LEval (TSort) | InternLM2-7b | https://arxiv.org/abs/2403.17297v1 | 16k | 4.3 |
Long-Context Understanding | Ada-LEval (TSort) | Claude-2 | null | 2k | 5.0 |
Long-Context Understanding | Ada-LEval (TSort) | Claude-2 | null | 4k | 5.0 |
Long-Context Understanding | Ada-LEval (TSort) | Claude-2 | null | 8k | 4.5 |
Long-Context Understanding | Ada-LEval (TSort) | Claude-2 | null | 16k | 3.0 |
Long-Context Understanding | Ada-LEval (TSort) | Claude-2 | null | 32k | 0.0 |
Long-Context Understanding | Ada-LEval (TSort) | Claude-2 | null | 64k | 0.0 |
Long-Context Understanding | Ada-LEval (TSort) | GPT-3.5-Turbo-1106 | null | 2k | 4.0 |
Long-Context Understanding | Ada-LEval (TSort) | GPT-3.5-Turbo-1106 | null | 4k | 4.5 |
Long-Context Understanding | Ada-LEval (TSort) | GPT-3.5-Turbo-1106 | null | 8k | 4.5 |
Long-Context Understanding | Ada-LEval (TSort) | GPT-3.5-Turbo-1106 | null | 16k | 5.5 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM3-6b-32k | https://arxiv.org/abs/2210.02414v2 | 2k | 2.3 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM3-6b-32k | https://arxiv.org/abs/2210.02414v2 | 4k | 2.4 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM3-6b-32k | https://arxiv.org/abs/2210.02414v2 | 8k | 2.0 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM3-6b-32k | https://arxiv.org/abs/2210.02414v2 | 16k | 0.7 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM2-6b-32k | https://arxiv.org/abs/2210.02414v2 | 2k | 0.9 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM2-6b-32k | https://arxiv.org/abs/2210.02414v2 | 4k | 0.2 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM2-6b-32k | https://arxiv.org/abs/2210.02414v2 | 8k | 0.7 |
Long-Context Understanding | Ada-LEval (TSort) | ChatGLM2-6b-32k | https://arxiv.org/abs/2210.02414v2 | 16k | 0.9 |
Period Estimation | OmniArt | OmniArt | http://arxiv.org/abs/1708.00684v1 | Mean absolute error | 77.9 |
Period Estimation | OmniArt | ResNet-50 | http://arxiv.org/abs/1708.00684v1 | Mean absolute error | 79.3 |
Inductive knowledge graph completion | Wikidata5m-ind | BLP-SimplE | https://arxiv.org/abs/2010.03496v3 | MRR | 0.493 |
Inductive knowledge graph completion | Wikidata5m-ind | BLP-SimplE | https://arxiv.org/abs/2010.03496v3 | Hits@1 | 0.289 |
Inductive knowledge graph completion | Wikidata5m-ind | KEPLER-Wiki-rel | https://arxiv.org/abs/1911.06136v3 | Hits@10 | 0.73 |
Inductive knowledge graph completion | Wikidata5m-ind | KEPLER-Wiki-rel | https://arxiv.org/abs/1911.06136v3 | MRR | 0.402 |
Inductive knowledge graph completion | Wikidata5m-ind | KEPLER-Wiki-rel | https://arxiv.org/abs/1911.06136v3 | Hits@1 | 0.222 |
Inductive knowledge graph completion | Wikidata5m-ind | KEPLER-Wiki-rel | https://arxiv.org/abs/1911.06136v3 | Hits@3 | 0.514 |
Inductive knowledge graph completion | Wikidata5m-ind | BLP-ComplEx | https://arxiv.org/abs/2010.03496v3 | Hits@10 | 0.877 |
Inductive knowledge graph completion | Wikidata5m-ind | BLP-ComplEx | https://arxiv.org/abs/2010.03496v3 | Hits@3 | 0.664 |
Inductive knowledge graph completion | WN18RR-ind | BLP-TransE | https://arxiv.org/abs/2010.03496v3 | MRR | 0.285 |
Inductive knowledge graph completion | WN18RR-ind | BLP-TransE | https://arxiv.org/abs/2010.03496v3 | Hits@3 | 0.361 |
Inductive knowledge graph completion | WN18RR-ind | BLP-TransE | https://arxiv.org/abs/2010.03496v3 | Hit@10 | 0.58 |
Inductive knowledge graph completion | WN18RR-ind | BLP-ComplEx | https://arxiv.org/abs/2010.03496v3 | Hits@1 | 0.156 |
Inductive knowledge graph completion | FB15k-237-ind | BLP-TransE | https://arxiv.org/abs/2010.03496v3 | MRR | 0.195 |
Inductive knowledge graph completion | FB15k-237-ind | BLP-TransE | https://arxiv.org/abs/2010.03496v3 | Hit@1 | 0.113 |
Inductive knowledge graph completion | FB15k-237-ind | BLP-TransE | https://arxiv.org/abs/2010.03496v3 | Hits@3 | 0.213 |
Inductive knowledge graph completion | FB15k-237-ind | BLP-TransE | https://arxiv.org/abs/2010.03496v3 | Hits@10 | 0.363 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | TransE-Concat | https://arxiv.org/abs/2103.09430v3 | Validation MRR | 0.8494 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | TransE-Concat | https://arxiv.org/abs/2103.09430v3 | Test MRR | 85.48 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | ComplEx-Concat | https://arxiv.org/abs/2103.09430v3 | Validation MRR | 0.8425 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | ComplEx-Concat | https://arxiv.org/abs/2103.09430v3 | Test MRR | 0.8637 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | ComplEx-RoBERTa | https://arxiv.org/abs/2103.09430v3 | Validation MRR | 0.7052 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | ComplEx-RoBERTa | https://arxiv.org/abs/2103.09430v3 | Test MRR | 0.7186 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | TransE-RoBERTa | https://arxiv.org/abs/2103.09430v3 | Validation MRR | 0.6039 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | WikiKG90M-LSC | TransE-RoBERTa | https://arxiv.org/abs/2103.09430v3 | Test MRR | 0.6288 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | MarT_MKGformer | https://arxiv.org/abs/2210.00312v4 | MRR | 0.341 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | MKGformer | https://arxiv.org/abs/2210.00312v4 | MRR | 0.321 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | MarT_FLAVA | https://arxiv.org/abs/2210.00312v4 | MRR | 0.288 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | ViLBERT | https://arxiv.org/abs/2210.00312v4 | MRR | 0.287 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | IKRL (ANALOGY) | https://arxiv.org/abs/2210.00312v4 | MRR | 0.283 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | IKRL | https://arxiv.org/abs/2210.00312v4 | MRR | 0.274 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | ViLT | https://arxiv.org/abs/2210.00312v4 | MRR | 0.257 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | MARS (Multimodal Analogical Reasoning dataSet) | TransAE | https://arxiv.org/abs/2210.00312v4 | MRR | 0.223 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | JerichoWorld | Worldformer | https://arxiv.org/abs/2106.09608v2 | Set accuracy | 39.15 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | JerichoWorld | Q*BERT | https://openreview.net/forum?id=Y1YtS9MZA75 | Set accuracy | 32.78 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | JerichoWorld | GATA-W | https://arxiv.org/abs/2106.09608v2 | Set accuracy | 24.06 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | JerichoWorld | Seq2Seq | https://openreview.net/forum?id=Y1YtS9MZA75 | Set accuracy | 14.29 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | JerichoWorld | Rules | https://openreview.net/forum?id=Y1YtS9MZA75 | Set accuracy | 4.70 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | FB15k | HHolE | https://arxiv.org/abs/1811.01062v2 | MRR | .796 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs | FB15k | COMPLEX | http://arxiv.org/abs/1702.06879v2 | MRR | 0.587 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBP-5L (Greek) | JMAC | https://arxiv.org/abs/2210.08922v2 | MRR | 71.7 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBP-5L (Greek) | AlignKGC | https://arxiv.org/abs/2104.08804v1 | MRR | 69.4 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBP-5L (Greek) | SS-AGA | https://arxiv.org/abs/2203.14987v1 | MRR | 35.3 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBP-5L (English) | JMAC | https://arxiv.org/abs/2210.08922v2 | MRR | 44.6 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBP-5L (English) | AlignKGC | https://arxiv.org/abs/2010.03158v2 | MRR | 41.3 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBP-5L (English) | SS-AGA | https://arxiv.org/abs/2203.14987v1 | MRR | 32.1 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | FB15k-237 | KBGAT | https://arxiv.org/abs/1906.01195v1 | Hits@3 | 54 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | FB15k-237 | KBGAT | https://arxiv.org/abs/1906.01195v1 | Hits@10 | 62.6 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | FB15k-237 | HAKE | https://arxiv.org/abs/1911.09419v3 | Hits@10 | 54.2 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | FB15k-237 | PKGC | https://openreview.net/forum?id=_wHAe6eoT8 | Hits@10 | 48.7 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | FB15k-237 | KBAT | https://arxiv.org/abs/1906.01195v1 | Hits@1 | 46 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | FB15k-237 | KBAT | https://arxiv.org/abs/1906.01195v1 | MRR | 0.518 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | FB15k-237 | KBAT | https://arxiv.org/abs/1906.01195v1 | MR | 0.210 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBbook2014 | KTUP (soft) | http://arxiv.org/abs/1902.06236v1 | Hits@10 | 60.75 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DBbook2014 | KTUP (soft) | http://arxiv.org/abs/1902.06236v1 | Mean Rank | 499 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DPB-5L (French) | JMAC | https://arxiv.org/abs/2210.08922v2 | MRR | 64.5 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DPB-5L (French) | AlignKGC | https://arxiv.org/abs/2010.03158v2 | MRR | 59.5 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | DPB-5L (French) | SS-AGA | https://arxiv.org/abs/2203.14987v1 | MRR | 36.6 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | MovieLens 1M | KTUP (soft) | http://arxiv.org/abs/1902.06236v1 | Hits@10 | 48.9 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | MovieLens 1M | KTUP (soft) | http://arxiv.org/abs/1902.06236v1 | Mean Rank | 527 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | WN18RR | HAKE | https://arxiv.org/abs/1911.09419v3 | Hits@3 | 0.516 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | WN18RR | KBGAT | https://arxiv.org/abs/1906.01195v1 | Hits@1 | 0.361 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | WN18RR | KBGAT | https://arxiv.org/abs/1906.01195v1 | Hits@3 | 0.483 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion | WN18RR | KBGAT | https://arxiv.org/abs/1906.01195v1 | Hits@10 | 0.581 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion > Triple Classification | YAGO39K | TransC (bern) | http://arxiv.org/abs/1811.04588v1 | Accuracy | 93.8 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion > Triple Classification | YAGO39K | TransC (bern) | http://arxiv.org/abs/1811.04588v1 | F1-Score | 93.7 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion > Triple Classification | YAGO39K | TransC (bern) | http://arxiv.org/abs/1811.04588v1 | Precision | 94.8 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Knowledge Graph Completion > Triple Classification | YAGO39K | TransC (bern) | http://arxiv.org/abs/1811.04588v1 | Recall | 92.7 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Complex Query Answering | WD50K-QE | NQE | https://arxiv.org/abs/2211.13469v3 | AVGp-MRR | 0.7584 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Complex Query Answering | NELL995 | CQD-Beam | https://arxiv.org/abs/2011.03459v4 | Hits@3 2p | 0.350 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Complex Query Answering | NELL995 | CQD-Beam | https://arxiv.org/abs/2011.03459v4 | Hits@3 3p | 0.288 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Complex Query Answering | NELL995 | CQD-Beam | https://arxiv.org/abs/2011.03459v4 | Hits@3 ip | 0.171 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Complex Query Answering | NELL995 | CQD-Beam | https://arxiv.org/abs/2011.03459v4 | Hits@3 pi | 0.277 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Complex Query Answering | NELL995 | CQD-Beam | https://arxiv.org/abs/2011.03459v4 | Hits@3 up | 0.156 |
Inductive knowledge graph completion > Large Language Model > Knowledge Graphs > Complex Query Answering | NELL995 | CQD-CO | https://arxiv.org/abs/2011.03459v4 | Hits@3 1p | 0.667 |
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