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 51–100 of 161 papers

TitleStatusHype
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
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
Can a Hallucinating Model help in Reducing Human "Hallucination"?—0
Math Multiple Choice Question Generation via Human-Large Language Model Collaboration—0
A Closer Look at Classification Evaluation Metrics and a Critical Reflection of Common Evaluation PracticeCode0
Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning—0
Differential contributions of machine learning and statistical analysis to language and cognitive sciences—0
Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank—0
Axiomatic modeling of fixed proportion technologies—0
Breaking Boundaries: A Chronology with Future Directions of Women in Exercise Physiology Research, Centred on Pregnancy—0
SoK: On Gradient Leakage in Federated Learning—0
Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language ModelsCode0
Prompting the E-Brushes: Users as Authors in Generative AI—0
WatChat: Explaining perplexing programs by debugging mental modelsCode0
Clarify: Improving Model Robustness With Natural Language CorrectionsCode0
The Essential Role of Causality in Foundation World Models for Embodied AI—0
Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias—0
Distortions in Judged Spatial Relations in Large Language Models—0
Finnish 5th and 6th graders' misconceptions about Artificial Intelligence—0
Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review—0
Fine-tuning Language Models for Factuality—0
Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual ProgrammingCode0
Unraveling the Single Tangent Space Fallacy: An Analysis and Clarification for Applying Riemannian Geometry in Robot Learning—0
Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions—0
Can Large Language Models Provide Security & Privacy Advice? Measuring the Ability of LLMs to Refute MisconceptionsCode0
EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context LearningCode0
Towards a Rigorous Analysis of Mutual Information in Contrastive Learning—0
Using language models in the implicit automated assessment of mathematical short answer items—0
Characterizing Information Seeking Events in Health-Related Social Discourse—0
Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context LearningCode0
Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational DataCode0
Reliability Check: An Analysis of GPT-3's Response to Sensitive Topics and Prompt WordingCode0
Dear XAI Community, We Need to Talk! Fundamental Misconceptions in Current XAI Research—0
Justices for Information Bottleneck Theory—0
Clarifying System 1 & 2 through the Common Model of Cognition—0
Disproving XAI Myths with Formal Methods -- Initial Results—0
Human-centered trust framework: An HCI perspective—0
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