Papers Misconceptions
“Misconceptions” 태그가 달린 논문 161편 · 필터 해제
Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning
This paper explores the synergy between human cognition and Large Language Models (LLMs), highlighting how generative AI can drive personalized learning at scale. We discuss parallels between LLMs and human cognition, em…
MisconceptionsDecoding Knowledge in Large Language Models: A Framework for Categorization and Comprehension
Understanding how large language models (LLMs) acquire, retain, and apply knowledge remains an open challenge. This paper introduces a novel framework, K-(CSA)^2, which categorizes LLM knowledge along two dimensions: cor…
MisconceptionsA Graphical Approach to State Variable Selection in Off-policy Learning
Sequential decision problems are widely studied across many areas of science. A key challenge when learning policies from historical data - a practice commonly referred to as off-policy learning - is how to ``identify'' …
Causal InferenceDimensionality ReductionMisconceptionsReinforcement Learning (RL)+1Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation
The capability of Large Language Models (LLMs) to plan remains a topic of debate. Some critics argue that strategies to boost LLMs' reasoning skills are ineffective in planning tasks, while others report strong outcomes …
MisconceptionsLearning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning Distractor
Large multimodal models (LMMs) have shown remarkable performance in the visual commonsense reasoning (VCR) task, which aims to answer a multiple-choice question based on visual commonsense within an image. However, the a…
MisconceptionsMultiple-choiceVisual Commonsense ReasoningDeveloper Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development
Despite the utility that Generative AI (GenAI) tools provide for tasks such as writing code, the use of these tools raises important legal questions and potential risks, particularly those associated with copyright law. …
MisconceptionsSurveyAutomatic Generation of Question Hints for Mathematics Problems using Large Language Models in Educational Technology
The automatic generation of hints by Large Language Models (LLMs) within Intelligent Tutoring Systems (ITSs) has shown potential to enhance student learning. However, generating pedagogically sound hints that address stu…
MathMisconceptionsA Study on Characterization of Near-Field Sub-Regions For Phased-Array Antennas
We characterize three near-field sub-regions for phased array antennas by elaborating on the boundaries {\it Fraunhofer}, {\it radial-focal}, and {\it non-radiating} distances. The {\it Fraunhofer distance} which is the …
MisconceptionsLLM-based Cognitive Models of Students with Misconceptions
Accurately modeling student cognition is crucial for developing effective AI-driven educational technologies. A key challenge is creating realistic student models that satisfy two essential properties: (1) accurately rep…
MisconceptionsThe Future of Learning in the Age of Generative AI: Automated Question Generation and Assessment with Large Language Models
In recent years, large language models (LLMs) and generative AI have revolutionized natural language processing (NLP), offering unprecedented capabilities in education. This chapter explores the transformative potential …
MisconceptionsMultiple-choiceQuestion GenerationQuestion-GenerationBenchmark Inflation: Revealing LLM Performance Gaps Using Retro-Holdouts
The training data for many Large Language Models (LLMs) is contaminated with test data. This means that public benchmarks used to assess LLMs are compromised, suggesting a performance gap between benchmark scores and act…
Holdout SetMisconceptionsTruthfulQAListening to Patients: A Framework of Detecting and Mitigating Patient Misreport for Medical Dialogue Generation
Medical Dialogue Systems aim to provide automated healthcare support through patient-agent conversations. Previous efforts typically regard patients as ideal users -- one who accurately and consistently reports their hea…
Dialogue GenerationHallucinationMisconceptionsResponse GenerationContrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills
People's decision-making abilities often fail to improve or may even erode when they rely on AI for decision-support, even when the AI provides informative explanations. We argue this is partly because people intuitively…
Decision MakingMisconceptionsA Thematic Framework for Analyzing Large-scale Self-reported Social Media Data on Opioid Use Disorder Treatment Using Buprenorphine Product
Background: One of the key FDA-approved medications for Opioid Use Disorder (OUD) is buprenorphine. Despite its popularity, individuals often report various information needs regarding buprenorphine treatment on social m…
MisconceptionsExploring Knowledge Tracing in Tutor-Student Dialogues using LLMs
Recent advances in large language models (LLMs) have led to the development of artificial intelligence (AI)-powered tutoring chatbots, showing promise in providing broad access to high-quality personalized education. Exi…
Knowledge TracingMisconceptionsEnhancing Knowledge Tracing with Concept Map and Response Disentanglement
In the rapidly advancing realm of educational technology, it becomes critical to accurately trace and understand student knowledge states. Conventional Knowledge Tracing (KT) models have mainly focused on binary response…
DisentanglementKnowledge TracingMisconceptionsMultiple-choiceClassifier-Free Guidance is a Predictor-Corrector
We investigate the theoretical foundations of classifier-free guidance (CFG). CFG is the dominant method of conditional sampling for text-to-image diffusion models, yet unlike other aspects of diffusion, it remains on sh…
DenoisingMisconceptionsProblems in AI, their roots in philosophy, and implications for science and society
Artificial Intelligence (AI) is one of today's most relevant emergent technologies. In view thereof, this paper proposes that more attention should be paid to the philosophical aspects of AI technology and its use. It is…
MisconceptionsPhilosophyNeural topology optimization: the good, the bad, and the ugly
Neural networks (NNs) hold great promise for advancing inverse design via topology optimization (TO), yet misconceptions about their application persist. This article focuses on neural topology optimization (neural TO), …
GPUMisconceptionsWhen big data actually are low-rank, or entrywise approximation of certain function-generated matrices
The article concerns low-rank approximation of matrices generated by sampling a smooth function of two $m$-dimensional variables. We identify several misconceptions surrounding a claim that, for a specific class of analy…
Misconceptions