SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 371380 of 399 papers

TitleStatusHype
Context and Humor: Understanding Amul advertisements of India0
Efficient illumination angle self-calibration in Fourier ptychography0
A Factoid Question Answering System for Vietnamese0
Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine ComprehensionCode0
Towards a Continuous Knowledge Learning Engine for Chatbots0
Distributed Fine-tuning of Language Models on Private Data0
Differentially Private Distributed Learning for Language Modeling Tasks0
Neural Regularized Domain Adaptation for Chinese Word Segmentation0
RDF2Vec: RDF Graph Embeddings and Their ApplicationsCode1
ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational KnowledgeCode2
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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