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 101–110 of 399 papers

TitleStatusHype
Large Language Models as a Tool for Mining Object Knowledge—0
Enhance Graph Alignment for Large Language Models—0
MANet: Fine-Tuning Segment Anything Model for Multimodal Remote Sensing Semantic Segmentation—0
Scalable Multi-Domain Adaptation of Language Models using Modular Experts—0
Thinking LLMs: General Instruction Following with Thought Generation—0
Distribution-aware Noisy-label Crack SegmentationCode0
Few Exemplar-Based General Medical Image Segmentation via Domain-Aware Selective Adaptation—0
Nudging: Inference-time Alignment of LLMs via Guided Decoding—0
DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object DetectionCode1
Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud LearningCode3
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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