SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 161170 of 399 papers

TitleStatusHype
Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case StudyCode0
Improving Personalized Search with Regularized Low-Rank Parameter UpdatesCode0
Exploiting Adapters for Cross-lingual Low-resource Speech RecognitionCode0
HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language ModelsCode0
ExplainCPE: A Free-text Explanation Benchmark of Chinese Pharmacist ExaminationCode0
Evaluating Prompt-based Question Answering for Object Prediction in the Open Research Knowledge GraphCode0
How Robust Are Router-LLMs? Analysis of the Fragility of LLM Routing CapabilitiesCode0
Knowledge graphs for empirical concept retrievalCode0
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small ModelsCode0
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language ModelsCode0
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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