SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 251260 of 399 papers

TitleStatusHype
ASLseg: Adapting SAM in the Loop for Semi-supervised Liver Tumor Segmentation0
Shifted Autoencoders for Point Annotation Restoration in Object Counting0
Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language ModelsCode0
AcademicGPT: Empowering Academic Research0
Towards Few-shot Out-of-Distribution Detection0
PELMS: Pre-training for Effective Low-Shot Multi-Document SummarizationCode0
Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case StudyCode0
Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI0
SAGE: Smart home Agent with Grounded Execution0
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained ModelCode0
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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