SOTAVerified

General Knowledge

This task aims to evaluate the ability of a model to answer general-knowledge questions.

Source: BIG-bench

Papers

Showing 281290 of 399 papers

TitleStatusHype
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language ModelsCode0
Learning with Recoverable ForgettingCode1
CC-Riddle: A Question Answering Dataset of Chinese Character RiddlesCode1
Knowledge-aware Neural Collective Matrix Factorization for Cross-domain Recommendation0
Connecting a French Dictionary from the Beginning of the 20th Century to WikidataCode0
Comprehensive Fair Meta-learned Recommender SystemCode0
SciDeBERTa: Learning DeBERTa for Science Technology Documents and Fine-Tuning Information Extraction TasksCode0
Task-Driven and Experience-Based Question Answering Corpus for In-Home Robot Application in the House3D Virtual EnvironmentCode0
Laughter During Cooperative and Competitive Games0
Prompt-aligned Gradient for Prompt TuningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy94.3Unverified
2Gopher-280B (few-shot, k=5)Accuracy93.9Unverified
3Chinchilla-70B (few-shot, k=5)Accuracy 85.7Unverified
4Gopher-280B (few-shot, k=5)Accuracy 84.8Unverified
5Gopher-280B (few-shot, k=5)Accuracy84.2Unverified
6Gopher-280B (few-shot, k=5)Accuracy 84.1Unverified
7Gopher-280B (few-shot, k=5)Accuracy 83.9Unverified
8Gopher-280B (few-shot, k=5)Accuracy83.3Unverified
9Gopher-280B (few-shot, k=5)Accuracy 81.8Unverified
10Gopher-280B (few-shot, k=5)Accuracy 81Unverified