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 311–320 of 399 papers

TitleStatusHype
Knowledgebra: An Algebraic Learning Framework for Knowledge Graph—0
TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning—0
Hierarchical Inductive Transfer for Continual Dialogue Learning—0
KMIR: A Benchmark for Evaluating Knowledge Memorization, Identification and Reasoning Abilities of Language Models—0
ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints—0
TURNER: The Uncertainty-based Retrieval Framework for Chinese NER—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Knowledge Matters: Radiology Report Generation with General and Specific Knowledge—0
Applying SoftTriple Loss for Supervised Language Model Fine Tuning—0
Hierarchical Inductive Transfer for Continual Dialogue 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