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 1–25 of 161 papers

TitleStatusHype
The Oversmoothing Fallacy: A Misguided Narrative in GNN Research—0
A Structured Unplugged Approach for Foundational AI Literacy in Primary EducationCode0
When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific ResearchCode0
Automated Identification of Logical Errors in Programs: Advancing Scalable Analysis of Student Misconceptions—0
Humans can learn to detect AI-generated texts, or at least learn when they can't—0
Harnessing Structured Knowledge: A Concept Map-Based Approach for High-Quality Multiple Choice Question Generation with Effective DistractorsCode0
Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative FilteringCode1
LLM Library Learning Fails: A LEGO-Prover Case Study—0
What is AI, what is it not, how we use it in physics and how it impacts... you—0
From Intuition to Understanding: Using AI Peers to Overcome Physics Misconceptions—0
Clarifying Misconceptions in COVID-19 Vaccine Sentiment and Stance Analysis and Their Implications for Vaccine Hesitancy Mitigation: A Systematic Review—0
How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit MisinformationCode0
Paths and Ambient Spaces in Neural Loss LandscapesCode0
Emergent Abilities in Large Language Models: A Survey—0
Analyzing Factors Influencing Driver Willingness to Accept Advanced Driver Assistance Systems—0
The Imitation Game for Educational AI—0
Retrieval-augmented systems can be dangerous medical communicators—0
Foundation Models in Computational Pathology: A Review of Challenges, Opportunities, and Impact—0
Knowledge Tracing in Programming Education Integrating Students' Questions—0
Generating Plausible Distractors for Multiple-Choice Questions via Student Choice Prediction—0
Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning—0
Decoding Knowledge in Large Language Models: A Framework for Categorization and Comprehension—0
A Graphical Approach to State Variable Selection in Off-policy Learning—0
Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation—0
Learning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning DistractorCode0
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