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 151–175 of 399 papers

TitleStatusHype
Differentially Private Distributed Learning for Language Modeling Tasks—0
AdaptGCD: Multi-Expert Adapter Tuning for Generalized Category Discovery—0
KAnoCLIP: Zero-Shot Anomaly Detection through Knowledge-Driven Prompt Learning and Enhanced Cross-Modal Integration—0
Knowledgebra: An Algebraic Learning Framework for Knowledge Graph—0
Deep Prompt Multi-task Network for Abuse Language Detection—0
Data structuring for the ontological modelling of wind energy systems—0
Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming—0
An Adaptive Deep Learning Framework for Day-ahead Forecasting of Photovoltaic Power Generation—0
DAML-ST5: Low Resource Style Transfer via Domain Adaptive Meta Learning—0
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era—0
Adapter-based Approaches to Knowledge-enhanced Language Models -- A Survey—0
Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI—0
BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization—0
Hierarchical Inductive Transfer for Continual Dialogue Learning—0
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation—0
Hierarchical Inductive Transfer for Continual Dialogue Learning—0
CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation—0
Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally—0
Intelligent Design 4.0: Paradigm Evolution Toward the Agentic AI Era—0
GRL-Prompt: Towards Knowledge Graph based Prompt Optimization via Reinforcement Learning—0
GOT4Rec: Graph of Thoughts for Sequential Recommendation—0
Autonomous Intelligent Software Development—0
AILS-NTUA at SemEval-2025 Task 4: Parameter-Efficient Unlearning for Large Language Models using Data Chunking—0
How to Complete Domain Tuning while Keeping General Ability in LLM: Adaptive Layer-wise and Element-wise Regularization—0
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level—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