SOTAVerified

General Knowledge

This task aims to evaluate the ability of a model to answer general-knowledge questions.

Source: BIG-bench

Papers

Showing 121130 of 399 papers

TitleStatusHype
Are Large Language Models a Good Replacement of Taxonomies?Code0
Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational KnowledgeCode0
Domain Generalization via Model-Agnostic Learning of Semantic FeaturesCode0
Leveraging Large Language Models for Automated Dialogue AnalysisCode0
Learning to Understand Phrases by Embedding the DictionaryCode0
Dive into the Resolution Augmentations and Metrics in Low Resolution Face Recognition: A Plain yet Effective New BaselineCode0
Distribution-aware Noisy-label Crack SegmentationCode0
Distilling Stereo Networks for Performant and Efficient Leaner NetworksCode0
Learning to Learn Variational Semantic MemoryCode0
Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov LogicCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy94.3Unverified
2Gopher-280B (few-shot, k=5)Accuracy93.9Unverified
3Chinchilla-70B (few-shot, k=5)Accuracy 85.7Unverified
4Gopher-280B (few-shot, k=5)Accuracy 84.8Unverified
5Gopher-280B (few-shot, k=5)Accuracy84.2Unverified
6Gopher-280B (few-shot, k=5)Accuracy 84.1Unverified
7Gopher-280B (few-shot, k=5)Accuracy 83.9Unverified
8Gopher-280B (few-shot, k=5)Accuracy83.3Unverified
9Gopher-280B (few-shot, k=5)Accuracy 81.8Unverified
10Gopher-280B (few-shot, k=5)Accuracy 81Unverified