Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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When Generative AI Meets Extended Reality: Enabling Scalable and Natural Interactions

An Explainable Market Integrity Monitoring System with Multi-Source Attention Signals and Transparent Scoring

Can We Trust LLM Detectors?

Embedding Retrofitting: Data Engineering for better RAG

Entropy-Tree: Tree-Based Decoding with Entropy-Guided Exploration

Elsewise: Authoring AI-Based Interactive Narrative with Possibility Space Visualization

Agentic Persona Control and Task State Tracking for Realistic User Simulation in Interactive Scenarios

LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback

Psychometric Comparability of LLM-Based Digital Twins

Scalable Board Expansion within a General Game System

Structured Hints for Sample-Efficient Lean Theorem Proving

Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

LLM Prompt Evaluation for Educational Applications

Multimodal Climate Disinformation Detection: Integrating Vision-Language Models with External Knowledge Sources

Controlling Long-Horizon Behavior in Language Model Agents with Explicit State Dynamics

Designing faster mixed integer linear programming algorithm via learning the optimal path

AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction Under Water Stress

Grounding Large Language Models in Reaction Knowledge Graphs for Synthesis Retrieval

Deja Vu in Plots: Leveraging Cross-Session Evidence with Retrieval-Augmented LLMs for Live Streaming Risk Assessment

Decoupling Return-to-Go for Efficient Decision Transformer

Natural Language-Driven Global Mapping of Martian Landforms

ICON: Invariant Counterfactual Optimization with Neuro-Symbolic Priors for Text-Based Person Search

EvoCUA: Evolving Computer Use Agents via Learning from Scalable Synthetic Experience

ErrorMap and ErrorAtlas: Charting the Failure Landscape of Large Language Models

Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification

VitalDiagnosis: AI-Driven Ecosystem for 24/7 Vital Monitoring and Chronic Disease Management

Creativity in the Age of AI: Rethinking the Role of Intentional Agency

Agentic Confidence Calibration

Off-Policy Actor-Critic with Sigmoid-Bounded Entropy for Real-World Robot Learning

Tabular Incremental Inference

PhysProver: Advancing Automatic Theorem Proving for Physics

Benchmarking Text-to-Python against Text-to-SQL: The Impact of Explicit Logic and Ambiguity

Investigation of the Generalisation Ability of Genetic Programming-evolved Scheduling Rules in Dynamic Flexible Job Shop Scheduling

AgentSM: Semantic Memory for Agentic Text-to-SQL

Improving Methodologies for LLM Evaluations Across Global Languages

Agentic Uncertainty Quantification

From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models

Improving Methodologies for Agentic Evaluations Across Domains: Leakage of Sensitive Information, Fraud and Cybersecurity Threats

Predictive Coding and Information Bottleneck for Hallucination Detection in Large Language Models

Agentic AI Governance and Lifecycle Management in Healthcare

CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models

Autonomous Business System via Neuro-symbolic AI

ALIGNAgent: Adaptive Learner Intelligence for Gap Identification and Next-step guidance

From Generative Engines to Actionable Simulators: The Imperative of Physical Grounding in World Models

TransportAgents: a multi-agents LLM framework for traffic accident severity prediction

The Dark Side of AI Transformers: Sentiment Polarization & the Loss of Business Neutrality by NLP Transformers

Tracking the Limits of Knowledge Propagation: How LLMs Fail at Multi-Step Reasoning with Conflicting Knowledge

MiRAGE: A Multiagent Framework for Generating Multimodal Multihop Question-Answer Dataset for RAG Evaluation

Reliability by design: quantifying and eliminating fabrication risk in LLMs. From generative to consultative AI: a comparative analysis in the legal domain and lessons for high-stakes knowledge bases

A tensor network formalism for neuro-symbolic AI

Not Your Typical Sycophant: The Elusive Nature of Sycophancy in Large Language Models

Beyond Prompting: Efficient and Robust Contextual Biasing for Speech LLMs via Logit-Space Integration (LOGIC)

GeMM-GAN: A Multimodal Generative Model Conditioned on Histopathology Images and Clinical Descriptions for Gene Expression Profile Generation

Logic Programming on Knowledge Graph Networks And its Application in Medical Domain

Prometheus Mind: Retrofitting Memory to Frozen Language Models

Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents

The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detection

Aeon: High-Performance Neuro-Symbolic Memory Management for Long-Horizon LLM Agents

DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Survey

Uncovering Latent Bias in LLM-Based Emergency Department Triage Through Proxy Variables

Gated Sparse Attention: Combining Computational Efficiency with Training Stability for Long-Context Language Models

AI/ML in 3GPP 5G Advanced -- Services and Architecture

CookAnything: A Framework for Flexible and Consistent Multi-Step Recipe Image Generation

Dynamic Correction of Erroneous State Estimates via Diffusion Bayesian Exploration

Concept-Guided Backdoor Attack on Vision Language Models

On the Holographic Geometry of Deterministic Computation

Decoding inner speech with an end-to-end brain-to-text neural interface

Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation

MindEval: Benchmarking Language Models on Multi-turn Mental Health Support

LAET: A Layer-wise Adaptive Ensemble Tuning Framework for Pretrained Language Models

FAST-CAD: A Fairness-Aware Framework for Non-Contact Stroke Diagnosis

Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale

SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control

MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling

Data-Augmented Deep Learning for Downhole Depth Sensing and Field Validation

Chinese Discharge Drug Recommendation in Metabolic Diseases with Large Language Models

Analysing Moral Bias in Finetuned LLMs through Mechanistic Interpretability

Orders in Chaos: Enhancing Large-Scale MoE LLM Serving with Data Movement Forecasting

Reinforce-Ada: An Adaptive Sampling Framework under Non-linear RL Objectives

TempoControl: Temporal Attention Guidance for Text-to-Video Models

AortaDiff: A Unified Multitask Diffusion Framework For Contrast-Free AAA Imaging

SoREX: Towards Self-Explainable Social Recommendation with Relevant Ego-Path Extraction

The AI Productivity Index (APEX)

Uncovering Grounding IDs: How External Cues Shape Multimodal Binding

Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization

V-CECE: Visual Counterfactual Explanations via Conceptual Edits

Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios

HARP: Hallucination Detection via Reasoning Subspace Projection

Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone

IPA: An Information-Reconstructive Input Projection Framework for Efficient Foundation Model Adaptation

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal

Retro-Expert: Collaborative Reasoning for Interpretable Retrosynthesis

A Survey on Diffusion Language Models

CodeNER: Code Prompting for Named Entity Recognition

ReSem3D: Refinable 3D Spatial Constraints via Fine-Grained Semantic Grounding for Generalizable Robotic Manipulation

VERIRAG: A Post-Retrieval Auditing of Scientific Study Summaries

SustainDiffusion: Optimising the Social and Environmental Sustainability of Stable Diffusion Models

LittleBit: Ultra Low-Bit Quantization via Latent Factorization

Real-Time Execution of Action Chunking Flow Policies

Teaching According to Students' Aptitude: Personalized Mathematics Tutoring via Persona-, Memory-, and Forgetting-Aware LLMs

Created by

Haebom

Category

Empty

저자

Yang Wu, Rujing Yao, Tong Zhang, Yufei Shi, Zhuoren Jiang, Zhushan Li, Xiaozhong Liu

개요

본 논문은 학생의 지식 변화를 동적으로 파악하여, 개인 맞춤형 수학 학습을 제공하는 LLM 기반 튜터링 시스템 TASA (Teaching According to Students' Aptitude)를 제안한다. TASA는 학생의 숙련도 프로필을 캡쳐하는 구조화된 학생 페르소나와 이전 학습 상호 작용을 기록하는 이벤트 메모리를 통합한다. 지속적인 망각 곡선과 지식 추적을 통해 각 학생의 숙달 상태를 동적으로 업데이트하고, 상황에 맞는 난이도로 질문과 설명을 생성한다.

시사점, 한계점

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시사점:

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학생의 망각 패턴과 학습자 프로파일을 모델링하여 LLM 기반 튜터링 시스템의 학습 성과와 적응성을 향상시킬 수 있음을 입증했다.

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수학 학습에서 학생의 숙달 수준과 인지적 유지에 맞춰 미세 조정된 지도가 중요하다는 점을 강조한다.

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TASA는 개인 맞춤형 수학 학습을 위한 효과적인 프레임워크를 제공한다.

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한계점:

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논문에서 구체적인 한계점이 명시되지 않음. (논문의 요약에서 한계점을 직접적으로 언급하지 않음)

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