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 251–275 of 399 papers

TitleStatusHype
KAER: A Knowledge Augmented Pre-Trained Language Model for Entity Resolution—0
PASS-FC: Progressive and Adaptive Search Scheme for Fact Checking of Comprehensive Claims—0
PhD Knowledge Not Required: A Reasoning Challenge for Large Language Models—0
Pilot: Building the Federated Multimodal Instruction Tuning Framework—0
PoE: a Panel of Experts for Generalized Automatic Dialogue Assessment—0
Pretraining and Updates of Domain-Specific LLM: A Case Study in the Japanese Business Domain—0
Proceedings of the ISCA/ITG Workshop on Diversity in Large Speech and Language Models—0
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning—0
Prompting Encoder Models for Zero-Shot Classification: A Cross-Domain Study in Italian—0
QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions—0
Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training—0
Rethinking Two Consensuses of the Transferability in Deep Learning—0
SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning—0
SAGE: Smart home Agent with Grounded Execution—0
SAM-Guided Robust Representation Learning for One-Shot 3D Medical Image Segmentation—0
Learning to Adapt SAM for Segmenting Cross-domain Point Clouds—0
SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation—0
Sample-Efficient Behavior Cloning Using General Domain Knowledge—0
Scalable Multi-Domain Adaptation of Language Models using Modular Experts—0
Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI—0
Score: A Rule Engine for the Scone Knowledge Base System—0
scReader: Prompting Large Language Models to Interpret scRNA-seq Data—0
Sculpting [CLS] Features for Pre-Trained Model-Based Class-Incremental Learning—0
Semi-Supervised Medical Image Segmentation via Knowledge Mining from Large Models—0
Sens-Merging: Sensitivity-Guided Parameter Balancing for Merging Large Language Models—0
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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