SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 201225 of 399 papers

TitleStatusHype
A Unified Industrial Large Knowledge Model Framework in Industry 4.0 and Smart Manufacturing0
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated LearningCode0
Prediction and Control in Continual Reinforcement LearningCode1
ASLseg: Adapting SAM in the Loop for Semi-supervised Liver Tumor Segmentation0
Shifted Autoencoders for Point Annotation Restoration in Object Counting0
A New Learning Paradigm for Foundation Model-based Remote Sensing Change DetectionCode1
MultiGPrompt for Multi-Task Pre-Training and Prompting on GraphsCode1
Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language ModelsCode0
AcademicGPT: Empowering Academic Research0
Towards Few-shot Out-of-Distribution Detection0
CurriculumLoc: Enhancing Cross-Domain Geolocalization through Multi-Stage RefinementCode1
Structured Chemistry Reasoning with Large Language ModelsCode1
PELMS: Pre-training for Effective Low-Shot Multi-Document SummarizationCode0
A Comprehensive Evaluation of GPT-4V on Knowledge-Intensive Visual Question AnsweringCode1
Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case StudyCode0
Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI0
SAGE: Smart home Agent with Grounded Execution0
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained ModelCode0
Motif-Based Prompt Learning for Universal Cross-Domain Recommendation0
Test-Time Self-Adaptive Small Language Models for Question AnsweringCode0
Learning to Adapt SAM for Segmenting Cross-domain Point Clouds0
Dobby: A Conversational Service Robot Driven by GPT-40
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning0
Key Factors Affecting European Reactions to AI in European Full and Flawed Democracies0
Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis0
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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