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 351–375 of 399 papers

TitleStatusHype
A Factoid Question Answering System for Vietnamese—0
Teaching Uncertainty Quantification in Machine Learning through Use Cases—0
Tencent AI Lab Machine Translation Systems for WMT20 Chat Translation Task—0
Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers—0
Generating Question Relevant Captions to Aid Visual Question Answering—0
A Dynamic Approach to Probabilistic Inference—0
The Scaling Law for LoRA Base on Mutual Information Upper Bound—0
Advancing Retrieval-Augmented Generation for Persian: Development of Language Models, Comprehensive Benchmarks, and Best Practices for Optimization—0
Explainable Hierarchical Imitation Learning for Robotic Drink Pouring—0
Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation—0
The Wisdom of Crowds in the Recollection of Order Information—0
Explicit Utilization of General Knowledge in Machine Reading Comprehension—0
The World in My Mind: Visual Dialog with Adversarial Multi-modal Feature Encoding—0
Exploring Safety-Utility Trade-Offs in Personalized Language Models—0
Evident: a Development Methodology and a Knowledge Base Topology for Data Mining, Machine Learning and General Knowledge Management—0
Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet?—0
Extending TWIG: Zero-Shot Predictive Hyperparameter Selection for KGEs based on Graph Structure—0
Extracting Unlearned Information from LLMs with Activation Steering—0
Thinking LLMs: General Instruction Following with Thought Generation—0
Fast constrained sampling in pre-trained diffusion models—0
AdaptGCD: Multi-Expert Adapter Tuning for Generalized Category Discovery—0
Few Exemplar-Based General Medical Image Segmentation via Domain-Aware Selective Adaptation—0
Evaluating Polish linguistic and cultural competency in large language models—0
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM—0
Evaluating Consistency and Reasoning Capabilities of 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