SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 301310 of 399 papers

TitleStatusHype
ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints0
QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions0
Autonomous Intelligent Software Development0
A Unified Industrial Large Knowledge Model Framework in Industry 4.0 and Smart Manufacturing0
Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis0
ASLseg: Adapting SAM in the Loop for Semi-supervised Liver Tumor Segmentation0
Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives0
Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training0
Ask Me Anything: Free-form Visual Question Answering Based on Knowledge from External Sources0
Visual Question Answering as Reading Comprehension0
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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