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 176–200 of 399 papers

TitleStatusHype
Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data—0
Boosting LLM Translation Skills without General Ability Loss via Rationale Distillation—0
Bootstrapping Cognitive Agents with a Large Language Model—0
Bridge-Coder: Unlocking LLMs' Potential to Overcome Language Gaps in Low-Resource Code—0
CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model Question Answering—0
Learning Electromagnetic Metamaterial Physics With ChatGPT—0
Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Driving—0
Collaborative ontology sharing and editing—0
Collective inference of the truth of propositions from crowd probability judgments—0
Colo-SCRL: Self-Supervised Contrastive Representation Learning for Colonoscopic Video Retrieval—0
Comparative Insights from 12 Machine Learning Models in Extracting Economic Ideology from Political Text—0
Composite Learning Units: Generalized Learning Beyond Parameter Updates to Transform LLMs into Adaptive Reasoners—0
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis—0
Constructing Enhanced Mutual Information for Online Class-Incremental Learning—0
Context and Humor: Understanding Amul advertisements of India—0
Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally—0
CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation—0
DAML-ST5: Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Data structuring for the ontological modelling of wind energy systems—0
Deep Prompt Multi-task Network for Abuse Language Detection—0
Differentially Private Distributed Learning for Language Modeling Tasks—0
DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning—0
Generating Question Relevant Captions to Aid Visual Question Answering—0
Distributed Fine-tuning of Language Models on Private Data—0
DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning—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