SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 4150 of 399 papers

TitleStatusHype
Semi-Supervised Medical Image Segmentation via Knowledge Mining from Large Models0
FuseChat-3.0: Preference Optimization Meets Heterogeneous Model FusionCode1
Keeping Yourself is Important in Downstream Tuning Multimodal Large Language ModelCode2
AILS-NTUA at SemEval-2025 Task 4: Parameter-Efficient Unlearning for Large Language Models using Data Chunking0
Evaluating Polish linguistic and cultural competency in large language models0
GeoEdit: Geometric Knowledge Editing for Large Language Models0
Sculpting [CLS] Features for Pre-Trained Model-Based Class-Incremental Learning0
Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model0
Sens-Merging: Sensitivity-Guided Parameter Balancing for Merging Large Language Models0
A Survey of Personalized Large Language Models: Progress and Future DirectionsCode2
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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