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 251–300 of 399 papers

TitleStatusHype
Generative Meta-Learning for Zero-Shot Relation Triplet Extraction—0
Better Question-Answering Models on a BudgetCode1
SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and MoreCode3
EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion RecognitionCode1
Colo-SCRL: Self-Supervised Contrastive Representation Learning for Colonoscopic Video Retrieval—0
Stop Words for Processing Software Engineering Documents: Do they Matter?—0
Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report GenerationCode1
Video Question Answering Using CLIP-Guided Visual-Text Attention—0
Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation—0
Dive into the Resolution Augmentations and Metrics in Low Resolution Face Recognition: A Plain yet Effective New BaselineCode0
Continual Pre-training of Language ModelsCode2
Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers—0
Adapting a Language Model While Preserving its General KnowledgeCode2
KAER: A Knowledge Augmented Pre-Trained Language Model for Entity Resolution—0
Few-Shot Class-Incremental Learning via Class-Aware Bilateral DistillationCode1
DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning—0
PoE: a Panel of Experts for Generalized Automatic Dialogue Assessment—0
A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and MultimodalCode3
Efficient Relation-aware Neighborhood Aggregation in Graph Neural Networks via Tensor DecompositionCode0
G-MAP: General Memory-Augmented Pre-trained Language Model for Domain TasksCode0
Rethinking Two Consensuses of the Transferability in Deep Learning—0
Knowledge Distillation for Detection Transformer with Consistent Distillation Points SamplingCode0
World Knowledge in Multiple Choice Reading ComprehensionCode0
Evident: a Development Methodology and a Knowledge Base Topology for Data Mining, Machine Learning and General Knowledge Management—0
Dominance-based Rough Set Approach, basic ideas and main trends—0
Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding—0
PANDA: Prompt Transfer Meets Knowledge Distillation for Efficient Model AdaptationCode1
Dual Modality Prompt Tuning for Vision-Language Pre-Trained ModelCode1
BinBert: Binary Code Understanding with a Fine-tunable and Execution-aware Transformer—0
Autonomous Intelligent Software Development—0
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language ModelsCode0
Learning with Recoverable ForgettingCode1
CC-Riddle: A Question Answering Dataset of Chinese Character RiddlesCode1
Knowledge-aware Neural Collective Matrix Factorization for Cross-domain Recommendation—0
Connecting a French Dictionary from the Beginning of the 20th Century to WikidataCode0
Comprehensive Fair Meta-learned Recommender SystemCode0
SciDeBERTa: Learning DeBERTa for Science Technology Documents and Fine-Tuning Information Extraction TasksCode0
Task-Driven and Experience-Based Question Answering Corpus for In-Home Robot Application in the House3D Virtual EnvironmentCode0
Laughter During Cooperative and Competitive Games—0
Prompt-aligned Gradient for Prompt TuningCode1
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Relphormer: Relational Graph Transformer for Knowledge Graph RepresentationsCode1
PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking—0
Seed-Guided Topic Discovery with Out-of-Vocabulary SeedsCode1
Knowledge Graph Contrastive Learning for RecommendationCode1
KALA: Knowledge-Augmented Language Model AdaptationCode1
Knowledgebra: An Algebraic Learning Framework for Knowledge Graph—0
TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning—0
Training Compute-Optimal Large Language ModelsCode6
Hierarchical Inductive Transfer for Continual Dialogue Learning—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