SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 271280 of 399 papers

TitleStatusHype
Rethinking Two Consensuses of the Transferability in Deep Learning0
Knowledge Distillation for Detection Transformer with Consistent Distillation Points SamplingCode0
World Knowledge in Multiple Choice Reading ComprehensionCode0
Evident: a Development Methodology and a Knowledge Base Topology for Data Mining, Machine Learning and General Knowledge Management0
Dominance-based Rough Set Approach, basic ideas and main trends0
Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding0
PANDA: Prompt Transfer Meets Knowledge Distillation for Efficient Model AdaptationCode1
Dual Modality Prompt Tuning for Vision-Language Pre-Trained ModelCode1
BinBert: Binary Code Understanding with a Fine-tunable and Execution-aware Transformer0
Autonomous Intelligent Software Development0
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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