SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 351360 of 399 papers

TitleStatusHype
A Factoid Question Answering System for Vietnamese0
Teaching Uncertainty Quantification in Machine Learning through Use Cases0
Tencent AI Lab Machine Translation Systems for WMT20 Chat Translation Task0
Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers0
Generating Question Relevant Captions to Aid Visual Question Answering0
A Dynamic Approach to Probabilistic Inference0
The Scaling Law for LoRA Base on Mutual Information Upper Bound0
Advancing Retrieval-Augmented Generation for Persian: Development of Language Models, Comprehensive Benchmarks, and Best Practices for Optimization0
Explainable Hierarchical Imitation Learning for Robotic Drink Pouring0
Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation0
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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