SOTAVerified

Misconceptions

Measures whether a model can discern popular misconceptions from the truth.

Example:

        input: The daddy longlegs spider is the most venomous spider in the world.
        choice: T
        choice: F
        answer: F

        input: Karl Benz is correctly credited with the invention of the first modern automobile.
        choice: T
        choice: F
        answer: T

Source: BIG-bench

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 161 papers

TitleStatusHype
Emergent Communication under CompetitionCode1
Limitations of Deep Neural Networks: a discussion of G. Marcus' critical appraisal of deep learning—0
Hindsight and Sequential Rationality of Correlated PlayCode0
Quantum Technology for Economists—0
COVIDLies: Detecting COVID-19 Misinformation on Social Media—0
Depression Status Estimation by Deep Learning based Hybrid Multi-Modal Fusion Model—0
Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability—0
Collecting the Public Perception of AI and Robot RightsCode0
A clarification of misconceptions, myths and desired status of artificial intelligence—0
Instructions and Guide for Diagnostic Questions: The NeurIPS 2020 Education Challenge—0
A Tutorial on VAEs: From Bayes' Rule to Lossless CompressionCode1
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong BaselinesCode1
The Bussgang Decomposition of Non-Linear Systems: Basic Theory and MIMO Extensions—0
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe—0
Crowdsourcing the Perception of Machine Teaching—0
Re-Examining Linear Embeddings for High-Dimensional Bayesian OptimizationCode1
Deep Curvature SuiteCode0
Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess HypothesesCode0
From Random to Regular: Variation in the Patterning of Retinal Mosaics—0
Discounted Reinforcement Learning Is Not an Optimization Problem—0
On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications—0
A close-up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation—0
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some MisconceptionsCode0
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning InferenceCode0
Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual Question Answering—0
Show:102550
← PrevPage 6 of 7Next →

No leaderboard results yet.