SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 226–250 of 399 papers

TitleStatusHype
Leveraging Large Language Models for Automated Dialogue AnalysisCode0
HAE-RAE Bench: Evaluation of Korean Knowledge in Language ModelsCode1
Overcoming Generic Knowledge Loss with Selective Parameter UpdateCode1
DR-Tune: Improving Fine-tuning of Pretrained Visual Models by Distribution Regularization with Semantic CalibrationCode1
PMET: Precise Model Editing in a TransformerCode1
Knowledge Prompt-tuning for Sequential RecommendationCode1
Learning to Model the World with Language—0
Multilingual Tourist Assistance using ChatGPT: Comparing Capabilities in Hindi, Telugu, and Kannada—0
A new algorithm for Subgroup Set Discovery based on Information Gain—0
Towards Task Sampler Learning for Meta-LearningCode1
Exploring the Potential of Large Language Models (LLMs) in Learning on GraphsCode2
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis—0
Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI—0
Can ChatGPT Enable ITS? The Case of Mixed Traffic Control via Reinforcement LearningCode0
GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language ModelCode1
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation LearningCode2
Bert4XMR: Cross-Market Recommendation with Bidirectional Encoder Representations from TransformerCode1
MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic SegmentationCode1
REFinD: Relation Extraction Financial DatasetCode0
ExplainCPE: A Free-text Explanation Benchmark of Chinese Pharmacist ExaminationCode0
Evaluating Prompt-based Question Answering for Object Prediction in the Open Research Knowledge GraphCode0
Investigating Forgetting in Pre-Trained Representations Through Continual Learning—0
Score: A Rule Engine for the Scone Knowledge Base System—0
On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code—0
"When Words Fail, Emojis Prevail": Generating Sarcastic Utterances with Emoji Using Valence Reversal and Semantic Incongruity—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy94.3—Unverified
2Gopher-280B (few-shot, k=5)Accuracy93.9—Unverified
3Chinchilla-70B (few-shot, k=5)Accuracy 85.7—Unverified
4Gopher-280B (few-shot, k=5)Accuracy 84.8—Unverified
5Gopher-280B (few-shot, k=5)Accuracy84.2—Unverified
6Gopher-280B (few-shot, k=5)Accuracy 84.1—Unverified
7Gopher-280B (few-shot, k=5)Accuracy 83.9—Unverified
8Gopher-280B (few-shot, k=5)Accuracy83.3—Unverified
9Gopher-280B (few-shot, k=5)Accuracy 81.8—Unverified
10Gopher-280B (few-shot, k=5)Accuracy 81—Unverified