SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 101110 of 399 papers

TitleStatusHype
Prompt-aligned Gradient for Prompt TuningCode1
Prompt Learning via Meta-RegularizationCode1
CC-Riddle: A Question Answering Dataset of Chinese Character RiddlesCode1
E2Map: Experience-and-Emotion Map for Self-Reflective Robot Navigation with Language ModelsCode1
SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained ModelsCode1
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?Code1
Generic Knowledge Boosted Pre-training For Remote Sensing ImagesCode1
PANDA: Prompt Transfer Meets Knowledge Distillation for Efficient Model AdaptationCode1
Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Driving0
Are LLMs Good Cryptic Crossword Solvers?0
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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