SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 181190 of 399 papers

TitleStatusHype
K-Link: Knowledge-Link Graph from LLMs for Enhanced Representation Learning in Multivariate Time-Series Data0
MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language ModelsCode1
Pruning neural network models for gene regulatory dynamics using data and domain knowledgeCode0
Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender EstimationCode3
Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and SundaneseCode1
Bootstrapping Cognitive Agents with a Large Language Model0
OMGEval: An Open Multilingual Generative Evaluation Benchmark for Large Language ModelsCode1
Inductive Graph Alignment Prompt: Bridging the Gap between Graph Pre-training and Inductive Fine-tuning From Spectral Perspective0
CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity KnowledgeCode2
Pre-training and Diagnosing Knowledge Base Completion ModelsCode1
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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