Word Sense Disambiguation On Words In Context
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
Modellname | Accuracy |
---|---|
lamini-lm-a-diverse-herd-of-distilled-models | 49.8 |
designing-effective-sparse-expert-models | 74 |
hungry-hungry-hippos-towards-language | 51.4 |
designing-effective-sparse-expert-models | 77.7 |
palm-scaling-language-modeling-with-pathways-1 | 78.8 |
lamini-lm-a-diverse-herd-of-distilled-models | 52.4 |
exploring-the-benefits-of-training-expert | 52.97 |
wic-10000-example-pairs-for-evaluating | 53.1 |
palm-2-technical-report-1 | 66.8 |
hungry-hungry-hippos-towards-language | 49.1 |
wic-10000-example-pairs-for-evaluating | 58.7 |
language-models-are-few-shot-learners | 49.4 |
toward-efficient-language-model-pretraining | 77.4 |
lamini-lm-a-diverse-herd-of-distilled-models | 64.7 |
knowledge-in-context-towards-knowledgeable | 52.40 |
wic-10000-example-pairs-for-evaluating | 57.7 |
hungry-hungry-hippos-towards-language | 51.4 |
exploring-the-limits-of-transfer-learning | 76.9 |
unifying-language-learning-paradigms | 77.3 |
n-grammer-augmenting-transformers-with-latent-1 | 56.1 |
guess-the-instruction-making-language-models | 50.42 |
deberta-decoding-enhanced-bert-with | 76.4 |
wic-10000-example-pairs-for-evaluating | 58.1 |
palm-2-technical-report-1 | 50.6 |
toward-efficient-language-model-pretraining | 77.1 |
fine-tuning-pre-trained-language-model-with | 85.3 |
sensebert-driving-some-sense-into-bert | 72.1 |
unifying-language-learning-paradigms | 49.8 |
wic-10000-example-pairs-for-evaluating | 59.3 |
alexatm-20b-few-shot-learning-using-a-large | 53.3 |
lamini-lm-a-diverse-herd-of-distilled-models | 63.8 |
deberta-decoding-enhanced-bert-with | 77.5 |
palm-2-technical-report-1 | 52.0 |
wic-10000-example-pairs-for-evaluating | 65.5 |
the-cot-collection-improving-zero-shot-and | 56.7 |
sensebert-driving-some-sense-into-bert | 70.3 |
lamini-lm-a-diverse-herd-of-distilled-models | 50.5 |