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 101–125 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
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
Selective Aggregation for Low-Rank Adaptation in Federated LearningCode2
Cascade Prompt Learning for Vision-Language Model AdaptationCode3
What Would You Ask When You First Saw a^2+b^2=c^2? Evaluating LLM on Curiosity-Driven Questioning—0
Bilingual Evaluation of Language Models on General Knowledge in University Entrance Exams with Minimal Contamination—0
E2Map: Experience-and-Emotion Map for Self-Reflective Robot Navigation with Language ModelsCode1
Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Driving—0
Aligning Medical Images with General Knowledge from Large Language ModelsCode1
How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language ModelsCode1
DIAGen: Diverse Image Augmentation with Generative ModelsCode1
Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data—0
CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation—0
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small ModelsCode0
RAGEval: Scenario Specific RAG Evaluation Dataset Generation FrameworkCode3
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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