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 241–250 of 399 papers

TitleStatusHype
Low-Resource Adaptation of Open-Domain Generative Chatbots—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
TRIM: Token Reduction and Inference Modeling for Cost-Effective Language Generation—0
MANet: Fine-Tuning Segment Anything Model for Multimodal Remote Sensing Semantic Segmentation—0
Mars: Situated Inductive Reasoning in an Open-World Environment—0
Composite Learning Units: Generalized Learning Beyond Parameter Updates to Transform LLMs into Adaptive Reasoners—0
Meta-Inductive Node Classification across Graphs—0
Unsupervised Neural Machine Translation for Low-Resource Domains via Meta-Learning—0
Comparative Insights from 12 Machine Learning Models in Extracting Economic Ideology from Political Text—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