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 26–50 of 161 papers

TitleStatusHype
Developer Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development—0
Automatic Generation of Question Hints for Mathematics Problems using Large Language Models in Educational Technology—0
A Study on Characterization of Near-Field Sub-Regions For Phased-Array Antennas—0
LLM-based Cognitive Models of Students with Misconceptions—0
The Future of Learning in the Age of Generative AI: Automated Question Generation and Assessment with Large Language Models—0
Benchmark Inflation: Revealing LLM Performance Gaps Using Retro-Holdouts—0
Listening to Patients: A Framework of Detecting and Mitigating Patient Misreport for Medical Dialogue Generation—0
Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills—0
A Thematic Framework for Analyzing Large-scale Self-reported Social Media Data on Opioid Use Disorder Treatment Using Buprenorphine Product—0
Exploring Knowledge Tracing in Tutor-Student Dialogues using LLMsCode1
Enhancing Knowledge Tracing with Concept Map and Response DisentanglementCode1
Classifier-Free Guidance is a Predictor-Corrector—0
Problems in AI, their roots in philosophy, and implications for science and society—0
Neural topology optimization: the good, the bad, and the ugly—0
When big data actually are low-rank, or entrywise approximation of certain function-generated matricesCode0
MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in EducationCode0
Formalising Anti-Discrimination Law in Automated Decision Systems—0
DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice QuestionsCode0
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language LearningCode0
Refining Skewed Perceptions in Vision-Language Models through Visual Representations—0
An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning—0
Toward In-Context Teaching: Adapting Examples to Students' Misconceptions—0
Common pitfalls to avoid while using multiobjective optimization in machine learning—0
Math Multiple Choice Question Generation via Human-Large Language Model Collaboration—0
Can a Hallucinating Model help in Reducing Human "Hallucination"?—0
Show:102550
← PrevPage 2 of 7Next →

No leaderboard results yet.