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 26–50 of 399 papers

TitleStatusHype
Adapting a Language Model While Preserving its General KnowledgeCode2
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational KnowledgeCode2
ConceptNet 5.5: An Open Multilingual Graph of General KnowledgeCode2
TaxoAdapt: Aligning LLM-Based Multidimensional Taxonomy Construction to Evolving Research CorporaCode1
HELM: Hyperbolic Large Language Models via Mixture-of-Curvature ExpertsCode1
A General Knowledge Injection Framework for ICD CodingCode1
A Dual-Space Framework for General Knowledge Distillation of Large Language ModelsCode1
FuseChat-3.0: Preference Optimization Meets Heterogeneous Model FusionCode1
Super-class guided Transformer for Zero-Shot Attribute ClassificationCode1
RAG with Differential PrivacyCode1
SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of ExpertsCode1
SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained ModelsCode1
Point-PRC: A Prompt Learning Based Regulation Framework for Generalizable Point Cloud AnalysisCode1
DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object DetectionCode1
E2Map: Experience-and-Emotion Map for Self-Reflective Robot Navigation with Language ModelsCode1
Aligning Medical Images with General Knowledge from Large Language ModelsCode1
How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language ModelsCode1
DIAGen: Diverse Image Augmentation with Generative ModelsCode1
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?Code1
Can Editing LLMs Inject Harm?Code1
ElecBench: a Power Dispatch Evaluation Benchmark for Large Language ModelsCode1
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMsCode1
To Forget or Not? Towards Practical Knowledge Unlearning for Large Language ModelsCode1
Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-Rank DecompositionCode1
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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