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 51–75 of 399 papers

TitleStatusHype
Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding—0
Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context AccurayCode3
PhD Knowledge Not Required: A Reasoning Challenge for Large Language Models—0
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM—0
Enabling Autonomic Microservice Management through Self-Learning Agents—0
CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model Question Answering—0
Sample-Efficient Behavior Cloning Using General Domain Knowledge—0
DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning ApproachCode0
Pilot: Building the Federated Multimodal Instruction Tuning Framework—0
The Breeze 2 Herd of Models: Traditional Chinese LLMs Based on Llama with Vision-Aware and Function-Calling CapabilitiesCode3
How to Complete Domain Tuning while Keeping General Ability in LLM: Adaptive Layer-wise and Element-wise Regularization—0
Generating Diverse Q&A Benchmarks for RAG Evaluation with DataMorgana—0
LLM4WM: Adapting LLM for Wireless Multi-Tasking—0
Comparative Insights from 12 Machine Learning Models in Extracting Economic Ideology from Political Text—0
Super-class guided Transformer for Zero-Shot Attribute ClassificationCode1
Collective inference of the truth of propositions from crowd probability judgments—0
Advancing Retrieval-Augmented Generation for Persian: Development of Language Models, Comprehensive Benchmarks, and Best Practices for Optimization—0
KAnoCLIP: Zero-Shot Anomaly Detection through Knowledge-Driven Prompt Learning and Enhanced Cross-Modal Integration—0
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric PerspectivesCode5
The Scaling Law for LoRA Base on Mutual Information Upper Bound—0
MoColl: Agent-Based Specific and General Model Collaboration for Image Captioning—0
KnowRA: Knowledge Retrieval Augmented Method for Document-level Relation Extraction with Comprehensive Reasoning Abilities—0
RAG with Differential PrivacyCode1
scReader: Prompting Large Language Models to Interpret scRNA-seq Data—0
Survey on Abstractive Text Summarization: Dataset, Models, and MetricsCode0
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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