SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 341350 of 399 papers

TitleStatusHype
Learning to Learn Variational Semantic MemoryCode0
Unsupervised Neural Machine Translation for Low-Resource Domains via Meta-Learning0
Patching as Translation: the Data and the MetaphorCode0
An Energy Ontology for Global City Indicators (ISO 37120)0
Domain Specific, Semi-Supervised Transfer Learning for Medical Imaging0
What's a Good Prediction? Challenges in evaluating an agent's knowledge0
What Does My QA Model Know? Devising Controlled Probes using Expert KnowledgeCode0
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation0
Joint Embedding Learning of Educational Knowledge Graphs0
Improving Multi-label Emotion Classification by Integrating both General and Domain-specific Knowledge0
Show:102550
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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