SOTAVerified

General Knowledge

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

Source: BIG-bench

Papers

Showing 131140 of 399 papers

TitleStatusHype
Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language ModelsCode0
Universal Item Tokenization for Transferable Generative Recommendation0
Generative Retrieval and Alignment Model: A New Paradigm for E-commerce Retrieval0
Understanding Inequality of LLM Fact-Checking over Geographic Regions with Agent and Retrieval models0
A Self-Supervised Learning of a Foundation Model for Analog Layout Design Automation0
Effective Skill Unlearning through Intervention and AbstentionCode0
Distilling Stereo Networks for Performant and Efficient Leaner NetworksCode0
LoRASculpt: Sculpting LoRA for Harmonizing General and Specialized Knowledge in Multimodal Large Language Models0
How Robust Are Router-LLMs? Analysis of the Fragility of LLM Routing CapabilitiesCode0
Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov LogicCode0
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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