SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 376399 of 399 papers

TitleStatusHype
HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language ModelsCode0
Can ChatGPT Enable ITS? The Case of Mixed Traffic Control via Reinforcement LearningCode0
How Robust Are Router-LLMs? Analysis of the Fragility of LLM Routing CapabilitiesCode0
Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine ComprehensionCode0
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language ModelsCode0
PROL : Rehearsal Free Continual Learning in Streaming Data via Prompt Online LearningCode0
G-MAP: General Memory-Augmented Pre-trained Language Model for Domain TasksCode0
Visual Question Answering: A Survey of Methods and DatasetsCode0
From Knowledge to Reasoning: Evaluating LLMs for Ionic Liquids Research in Chemical and Biological EngineeringCode0
Quantized Prompt for Efficient Generalization of Vision-Language ModelsCode0
World Knowledge in Multiple Choice Reading ComprehensionCode0
Foundation X: Integrating Classification, Localization, and Segmentation through Lock-Release Pretraining Strategy for Chest X-ray AnalysisCode0
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated LearningCode0
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained ModelCode0
Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case StudyCode0
REFinD: Relation Extraction Financial DatasetCode0
Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov LogicCode0
Exploiting Adapters for Cross-lingual Low-resource Speech RecognitionCode0
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference ContentCode0
Towards Knowledge-Augmented Visual Question AnsweringCode0
ExplainCPE: A Free-text Explanation Benchmark of Chinese Pharmacist ExaminationCode0
Evaluating Prompt-based Question Answering for Object Prediction in the Open Research Knowledge GraphCode0
DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning ApproachCode0
Survey on Abstractive Text Summarization: Dataset, Models, and MetricsCode0
Show:102550
← PrevPage 16 of 16Next →

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