SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 261270 of 399 papers

TitleStatusHype
Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training0
Rethinking Two Consensuses of the Transferability in Deep Learning0
SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning0
SAGE: Smart home Agent with Grounded Execution0
SAM-Guided Robust Representation Learning for One-Shot 3D Medical Image Segmentation0
Learning to Adapt SAM for Segmenting Cross-domain Point Clouds0
SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation0
Sample-Efficient Behavior Cloning Using General Domain Knowledge0
Scalable Multi-Domain Adaptation of Language Models using Modular Experts0
Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI0
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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