haebom
Daily Arxiv
전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.
M3DR: Towards Universal Multilingual Multimodal Document Retrieval
Physics-Driven Learning Framework for Tomographic Tactile Sensing
NAS-LoRA: Empowering Parameter-Efficient Fine-Tuning for Visual Foundation Models with Searchable Adaptation
Cell-cell communication inference and analysis: biological mechanisms, computational approaches, and future opportunities
ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms
AsymPuzl: An Asymmetric Puzzle for multi-agent cooperation
Text-Printed Image: Bridging the Image-Text Modality Gap for Text-centric Training of Large Vision-Language Models
Learning From Limited Data and Feedback for Cell Culture Process Monitoring: A Comparative Study
Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles
GalaxyDiT: Efficient Video Generation with Guidance Alignment and Adaptive Proxy in Diffusion Transformers
Multi-Aspect Knowledge-Enhanced Medical Vision-Language Pretraining with Multi-Agent Data Generation
World Models for Autonomous Navigation of Terrestrial Robots from LIDAR Observations
BookRAG: A Hierarchical Structure-aware Index-based Approach for Retrieval-Augmented Generation on Complex Documents
Better World Models Can Lead to Better Post-Training Performance
VS-Graph: Scalable and Efficient Graph Classification Using Hyperdimensional Computing
UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs
FireSentry: A Multi-Modal Spatio-temporal Benchmark Dataset for Fine-Grained Wildfire Spread Forecasting
HalluGen: Synthesizing Realistic and Controllable Hallucinations for Evaluating Image Restoration
Idea-Gated Transformers: Enforcing Semantic Coherence via Differentiable Vocabulary Pruning
ProtoEFNet: Dynamic Prototype Learning for Inherently Interpretable Ejection Fraction Estimation in Echocardiography
Single-Round Scalable Analytic Federated Learning
Cache What Lasts: Token Retention for Memory-Bounded KV Cache in LLMs
NavMapFusion: Diffusion-based Fusion of Navigation Maps for Online Vectorized HD Map Construction
Retrofitting Earth System Models with Cadence-Limited Neural Operator Updates
Robust Tabular Foundation Models
HydroDCM: Hydrological Domain-Conditioned Modulation for Cross-Reservoir Inflow Prediction
Adaptive Regime-Switching Forecasts with Distribution-Free Uncertainty: Deep Switching State-Space Models Meet Conformal Prediction
BlendedNet++: A Large-Scale Blended Wing Body Aerodynamics Dataset and Benchmark
Thucy: An LLM-based Multi-Agent System for Claim Verification across Relational Databases
PyroFocus: A Deep Learning Approach to Real-Time Wildfire Detection in Multispectral Remote Sensing Imagery
Learning Network Sheaves for AI-native Semantic Communication
SPARK: Stepwise Process-Aware Rewards for Reference-Free Reinforcement Learning
How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy
InvertiTune: High-Quality Data Synthesis for Cost-Effective Single-Shot Text-to-Knowledge Graph Generation
Ultra-Strong Gradient Diffusion MRI with Self-Supervised Learning for Prostate Cancer Characterization
Plantain: Plan-Answer Interleaved Reasoning
Culture Affordance Atlas: Reconciling Object Diversity Through Functional Mapping
Atomic Diffusion Models for Small Molecule Structure Elucidation from NMR Spectra
Mitigating Intra- and Inter-modal Forgetting in Continual Learning of Unified Multimodal Models
Lost in Modality: Evaluating the Effectiveness of Text-Based Membership Inference Attacks on Large Multimodal Models
Beyond Additivity: Sparse Isotonic Shapley Regression toward Nonlinear Explainability
PanFoMa: A Lightweight Foundation Model and Benchmark for Pan-Cancer
The BEAT-CF Causal Model: A model for guiding the design of trials and observational analyses of cystic fibrosis exacerbations
E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing
Public Sentiment Analysis of Traffic Management Policies in Knoxville: A Social Media Driven Study
Dynamic Correction of Erroneous State Estimates via Diffusion Bayesian Exploration
ALARM: Automated MLLM-Based Anomaly Detection in Complex-EnviRonment Monitoring with Uncertainty Quantification
Ensemble Privacy Defense for Knowledge-Intensive LLMs against Membership Inference Attacks
QGShap: Quantum Acceleration for Faithful GNN Explanations
Community Quality and Influence Maximization: An Empirical Study
Password-Activated Shutdown Protocols for Misaligned Frontier Agents
When Harmful Content Gets Camouflaged: Unveiling Perception Failure of LVLMs with CamHarmTI
Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation
Alleviating Choice Supportive Bias in LLM with Reasoning Dependency Generation
AtomDisc: An Atom-level Tokenizer that Boosts Molecular LLMs and Reveals Structure--Property Associations
Irresponsible AI: big tech's influence on AI research and associated impacts
Will Power Return to the Clouds? From Divine Authority to GenAI Authority
Economies of Open Intelligence: Tracing Power & Participation in the Model Ecosystem
PretopoMD: Pretopology-based Mixed Data Hierarchical Clustering
Mixed Data Clustering Survey and Challenges
Hierarchical clustering of complex energy systems using pretopology
Echoes of AI Harms: A Human-LLM Synergistic Framework for Bias-Driven Harm Anticipation
Quantifying the Potential to Escape Filter Bubbles: A Behavior-Aware Measure via Contrastive Simulation
Optimizing Life Sciences Agents in Real-Time using Reinforcement Learning
A note on the impossibility of conditional PAC-efficient reasoning in large language models
Delta Sampling: Data-Free Knowledge Transfer Across Diffusion Models
Physics-informed self-supervised learning for predictive modeling of coronary artery digital twins
Energy-Efficient Federated Learning via Adaptive Encoder Freezing for MRI-to-CT Conversion: A Green AI-Guided Research
Mitigating hallucinations and omissions in LLMs for invertible problems: An application to hardware logic design automation
Entropy-Based Measurement of Value Drift and Alignment Work in Large Language Models
AI-Driven Document Redaction in UK Public Authorities: Implementation Gaps, Regulatory Challenges, and the Human Oversight Imperative
Benchmark for Planning and Control with Large Language Model Agents: Blocksworld with Model Context Protocol
Autonomous Agents and Policy Compliance: A Framework for Reasoning About Penalties
A Hierarchical Tree-based approach for creating Configurable and Static Deep Research Agent (Static-DRA)
Omni-AutoThink: Adaptive Multimodal Reasoning via Reinforcement Learning
RoCo: Role-Based LLMs Collaboration for Automatic Heuristic Design
MemVerse: Multimodal Memory for Lifelong Learning Agents
DeepRule: An Integrated Framework for Automated Business Rule Generation via Deep Predictive Modeling and Hybrid Search Optimization
EnCompass: Enhancing Agent Programming with Search Over Program Execution Paths
Reason-Plan-ReAct: A Reasoner-Planner Supervising a ReAct Executor for Complex Enterprise Tasks
PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks
Multi-Agent Reinforcement Learning with Communication-Constrained Priors
Multimodal Reinforcement Learning with Agentic Verifier for AI Agents
Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
Prior preferences in active inference agents: soft, hard, and goal shaping
When Do Symbolic Solvers Enhance Reasoning in Large Language Models?
Beyond the Black Box: A Cognitive Architecture for Explainable and Aligned AI
Exploring Syntropic Frameworks in AI Alignment: A Philosophical Investigation
Kardia-R1: Unleashing LLMs to Reason toward Understanding and Empathy for Emotional Support via Rubric-as-Judge Reinforcement Learning
Proactive Agentic Whiteboards: Enhancing Diagrammatic Learning
Beyond Greenfield: The D3 Framework for AI-Driven Productivity in Brownfield Engineering
Look, Recite, Then Answer: Enhancing VLM Performance via Self-Generated Knowledge Hints
HBLLM: A Haar-Based Approach for Accurate Structured 1-Bit Quantized LLMs
Limitations of Using Identical Distributions for Training and Testing When Learning Boolean Functions
BioArc: Discovering Optimal Neural Architectures for Biological Foundation Models
MIMIC-MJX: Neuromechanical Emulation of Animal Behavior
Multimodal Continual Learning with MLLMs from Multi-scenario Perspectives
PersonaAgent with GraphRAG: Community-Aware Knowledge Graphs for Personalized LLM
Generative AI in Sociological Research: State of the Discipline
MRI Super-Resolution with Deep Learning: A Comprehensive Survey
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PresentCoach: Dual-Agent Presentation Coaching through Exemplars and Interactive Feedback
Created by
Haebom
Category
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저자
Sirui Chen, Jinsong Zhou, Xinli Xu, Xiaoyu Yang, Litao Guo, Ying-Cong Chen
개요
본 논문은 발표 기술 향상을 위한 듀얼 에이전트 시스템을 소개합니다. 이 시스템은 이상적인 발표 모델을 생성하는 Ideal Presentation Agent와 사용자의 발표를 평가하고 피드백을 제공하는 Coach Agent로 구성됩니다. Coach Agent는 청중의 반응을 시뮬레이션하는 Audience Agent를 포함하여 OIS 형식의 구조화된 피드백을 제공하며, 발표 기술 개발을 위한 몰입형 학습 경험을 제공합니다.
시사점, 한계점
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시사점:
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AI 기반 에이전트를 활용하여 발표 기술 개발을 위한 몰입형 학습 환경 제공.
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Ideal Presentation Agent를 통한 이상적인 발표 모델 생성 및 학습.
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Coach Agent를 통한 상세한 피드백 제공 (OIS 형식).
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Audience Agent를 통한 청중 반응 시뮬레이션 및 실질적인 피드백.
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교육 및 전문 분야에서 발표 기술 향상에 기여 가능성.
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한계점:
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구체적인 시스템 성능 데이터 및 평가 결과 부재 가능성.
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다양한 발표 스타일 및 청중 유형에 대한 적응성 제한.
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음성 복제 및 오류 처리 메커니즘의 한계.
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개인 정보 보호 및 윤리적 문제 고려 필요.
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