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 101–125 of 161 papers

TitleStatusHype
Challenges and Trends in User Trust Discourse in AI—0
On the lifting and reconstruction of nonlinear systems with multiple invariant sets—0
Demystifying Misconceptions in Social Bots Research—0
Succinct Representations for Concepts—0
Response to Moffat's Comment on "Towards Meaningful Statements in IR Evaluation: Mapping Evaluation Measures to Interval Scales"—0
Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics—0
Improving Unsupervised Video Object Segmentation with Motion-Appearance Synergy—0
The Monitor Model and its Misconceptions: A Clarification—0
Machine Learning Students Overfit to Overfitting—0
Dynamics and triggers of misinformation on vaccines—0
Response to: Significance and stability of deep learning-based identification of subtypes within major psychiatric disorders. Molecular Psychiatry (2022)—0
How Useful are Gradients for OOD Detection Really?—0
A Weakly-Supervised Iterative Graph-Based Approach to Retrieve COVID-19 Misinformation TopicsCode0
From Solution Synthesis to Student Attempt Synthesis for Block-Based Visual Programming TasksCode0
Rectified Max-Value Entropy Search for Bayesian Optimization—0
Biometric recognition: why not massively adopted yet?—0
Metagenomic Analysis using Phylogenetic Placement -- A Review of the First Decade—0
Resolving conceptual issues in Modern Coexistence TheoryCode0
Big Data is not the New Oil: Common Misconceptions about Population Data—0
Demystifying Ten Big Ideas and Rules Every Fire Scientist & Engineer Should Know About Blackbox, Whitebox & Causal Artificial Intelligence—0
End-to-End Annotator Bias Approximation on Crowdsourced Single-Label Sentiment AnalysisCode0
The kernel perspective on dynamic mode decomposition—0
Laplace Redux - Effortless Bayesian Deep Learning—0
Beyond Fair Pay: Ethical Implications of NLP Crowdsourcing—0
Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networksCode0
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