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 226–250 of 399 papers

TitleStatusHype
Learning Knowledge Graphs for Question Answering through Conversational Dialog—0
Learning Physical Common Sense as Knowledge Graph Completion via BERT Data Augmentation and Constrained Tucker Factorization—0
Transfer learning of chaotic systems—0
Learning to Model the World with Language—0
Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally—0
Learning to Specialize with Knowledge Distillation for Visual Question Answering—0
Transformer Based Bengali Chatbot Using General Knowledge Dataset—0
Learning Unknown Spoof Prompts for Generalized Face Anti-Spoofing Using Only Real Face Images—0
Context and Humor: Understanding Amul advertisements of India—0
Who You Are Matters: Bridging Topics and Social Roles via LLM-Enhanced Logical Recommendation—0
Leveraging Large Language Models for enhanced personalised user experience in Smart Homes—0
LLM4WM: Adapting LLM for Wireless Multi-Tasking—0
Constructing Enhanced Mutual Information for Online Class-Incremental Learning—0
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis—0
LoRASculpt: Sculpting LoRA for Harmonizing General and Specialized Knowledge in Multimodal Large Language Models—0
Low-Resource Adaptation of Open-Domain Generative Chatbots—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
TRIM: Token Reduction and Inference Modeling for Cost-Effective Language Generation—0
MANet: Fine-Tuning Segment Anything Model for Multimodal Remote Sensing Semantic Segmentation—0
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
Meta-Inductive Node Classification across Graphs—0
Unsupervised Neural Machine Translation for Low-Resource Domains via Meta-Learning—0
Comparative Insights from 12 Machine Learning Models in Extracting Economic Ideology from Political Text—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