SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 8190 of 399 papers

TitleStatusHype
KALA: Knowledge-Augmented Language Model AdaptationCode1
KGPT: Knowledge-Grounded Pre-Training for Data-to-Text GenerationCode1
Aligning Medical Images with General Knowledge from Large Language ModelsCode1
DIAGen: Diverse Image Augmentation with Generative ModelsCode1
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD DetectionCode1
CurriculumLoc: Enhancing Cross-Domain Geolocalization through Multi-Stage RefinementCode1
ElecBench: a Power Dispatch Evaluation Benchmark for Large Language ModelsCode1
DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object DetectionCode1
Knowledge Graph Contrastive Learning for RecommendationCode1
Dual Modality Prompt Tuning for Vision-Language Pre-Trained ModelCode1
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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