SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 231240 of 399 papers

TitleStatusHype
Knowledge Prompt-tuning for Sequential RecommendationCode1
Learning to Model the World with Language0
Multilingual Tourist Assistance using ChatGPT: Comparing Capabilities in Hindi, Telugu, and Kannada0
A new algorithm for Subgroup Set Discovery based on Information Gain0
Towards Task Sampler Learning for Meta-LearningCode1
Exploring the Potential of Large Language Models (LLMs) in Learning on GraphsCode2
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis0
Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI0
Can ChatGPT Enable ITS? The Case of Mixed Traffic Control via Reinforcement LearningCode0
GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language ModelCode1
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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