SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 191–200 of 399 papers

TitleStatusHype
Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally—0
CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation—0
DAML-ST5: Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Data structuring for the ontological modelling of wind energy systems—0
Deep Prompt Multi-task Network for Abuse Language Detection—0
Differentially Private Distributed Learning for Language Modeling Tasks—0
DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning—0
Generating Question Relevant Captions to Aid Visual Question Answering—0
Distributed Fine-tuning of Language Models on Private Data—0
DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning—0
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Benchmark Results

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