Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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HPC Digital Twins for Evaluating Scheduling Policies, Incentive Structures and their Impact on Power and Cooling

NLKI: A lightweight Natural Language Knowledge Integration Framework for Improving Small VLMs in Commonsense VQA Tasks

Interact-Custom: Customized Human Object Interaction Image Generation

A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation

MIDAS: Multimodal Interactive Digital-humAn Synthesis via Real-time Autoregressive Video Generation

From Tabula Rasa to Emergent Abilities: Discovering Robot Skills via Real-World Unsupervised Quality-Diversity

Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks

STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems

LLMs Can't Handle Peer Pressure: Crumbling under Multi-Agent Social Interactions

Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning

Modality-Specific Speech Enhancement and Noise-Adaptive Fusion for Acoustic and Body-Conduction Microphone Framework

Humans Perceive Wrong Narratives from AI Reasoning Texts

SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning

Pareto Actor-Critic for Communication and Computation Co-Optimization in Non-Cooperative Federated Learning Services

Learning to Drive Ethically: Embedding Moral Reasoning into Autonomous Driving

Generative AI Against Poaching: Latent Composite Flow Matching for Wildlife Conservation

Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)

Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics

Steering Towards Fairness: Mitigating Political Bias in LLMs

Dynamic Context Compression for Efficient RAG

Irredundant $k$-Fold Cross-Validation

Prompt Engineering and the Effectiveness of Large Language Models in Enhancing Human Productivity

A Highly Clean Recipe Dataset with Ingredient States Annotation for State Probing Task

Entropy-Memorization Law: Evaluating Memorization Difficulty of Data in LLMs

The Joys of Categorical Conformal Prediction

Adversarial Manipulation of Reasoning Models using Internal Representations

Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models

A Hybrid Artificial Intelligence Method for Estimating Flicker in Power Systems (Changes are marked)

GLProtein: Global-and-Local Structure Aware Protein Representation Learning

Program Semantic Inequivalence Game with Large Language Models

DSO: Aligning 3D Generators with Simulation Feedback for Physical Soundness

Improving Quantization with Post-Training Model Expansion

Safe and Efficient Social Navigation through Explainable Safety Regions Based on Topological Features

A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing

Federated nnU-Net for Privacy-Preserving Medical Image Segmentation

ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation

Enhancing Automated Loop Invariant Generation for Complex Programs with Large Language Models

RevPRAG: Revealing Poisoning Attacks in Retrieval-Augmented Generation through LLM Activation Analysis

Categorical Data Clustering via Value Order Estimated Distance Metric Learning

Application of AI to formal methods - an analysis of current trends

Reconsidering the Performance of GAE in Link Prediction

See then Tell: Enhancing Key Information Extraction with Vision Grounding

Enhancing Natural Language Inference Performance with Knowledge Graph for COVID-19 Automated Fact-Checking in Indonesian Language

Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics

FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference

SoAy: A Solution-based LLM API-using Methodology for Academic Information Seeking

Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study

Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off

Network Formation and Dynamics Among Multi-LLMs

NetGPT: Generative Pretrained Transformer for Network Traffic

OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset

Explainability of Text Processing and Retrieval Methods: A Survey

The Ramon Llull's Thinking Machine for Automated Ideation

RLMR: Reinforcement Learning with Mixed Rewards for Creative Writing

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

MSARL: Decoupling Reasoning and Tool Use with Multi-Small-Agent Reinforcement Learning

Automated Algorithmic Discovery for Gravitational-Wave Detection Guided by LLM-Informed Evolutionary Monte Carlo Tree Search

Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess

Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground

Possible Principles for Aligned Structure Learning Agents

OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale

Prompt-to-Product: Generative Assembly via Bimanual Manipulation

OnGoal: Tracking and Visualizing Conversational Goals in Multi-Turn Dialogue with Large Language Models

Mixture of Contexts for Long Video Generation

FakeParts: a New Family of AI-Generated DeepFakes

Enabling Equitable Access to Trustworthy Financial Reasoning

Veritas: Generalizable Deepfake Detection via Pattern-Aware Reasoning

Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop

Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance

ChainReaction! Structured Approach with Causal Chains as Intermediate Representations for Improved and Explainable Causal Video Question Answering

Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Trees

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts

WoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations

ProactiveEval: A Unified Evaluation Framework for Proactive Dialogue Agents

Research Challenges in Relational Database Management Systems for LLM Queries

Quantum Verifiable Rewards for Post-Training Qiskit Code Assistant

AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning

JADES: A Universal Framework for Jailbreak Assessment via Decompositional Scoring

Learning Primitive Embodied World Models: Towards Scalable Robotic Learning

Multi-Agent Penetration Testing AI for the Web

Uncertainty Aware-Predictive Control Barrier Functions: Safer Human Robot Interaction through Probabilistic Motion Forecasting

Exploring Machine Learning and Language Models for Multimodal Depression Detection

Speech Emotion Recognition via Entropy-Aware Score Selection

Surfel-based 3D Registration with Equivariant SE(3) Features

Evaluating Compositional Generalisation in VLMs and Diffusion Models

Safer Skin Lesion Classification with Global Class Activation Probability Map Evaluation and SafeML

Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI

Signs of Struggle: Spotting Cognitive Distortions across Language and Register

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection

Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding

SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer

Occlusion Robustness of CLIP for Military Vehicle Classification

SeqVLM: Proposal-Guided Multi-View Sequences Reasoning via VLM for Zero-Shot 3D Visual Grounding

Provable Benefits of In-Tool Learning for Large Language Models

${C}^{3}$-GS: Learning Context-aware, Cross-dimension, Cross-scale Feature for Generalizable Gaussian Splatting

Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol

EEGDM: Learning EEG Representation with Latent Diffusion Model

Generative Annotation for ASR Named Entity Correction

MobileCLIP2: Improving Multi-Modal Reinforced Training

Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning

"Stack It Up!": 3D Stable Structure Generation from 2D Hand-drawn Sketch

Created by

Haebom

저자

Yiqing Xu, Linfeng Li, Cunjun Yu, David Hsu

개요

StackItUp은 비전문가가 2D 손그림 스케치만으로 복잡한 3D 구조를 지정할 수 있게 해주는 시스템입니다. 정확한 3D 블록 배치를 위해 구조 분석 및 CAD와 같은 전문가 도구가 필요한 기존 로봇 조작 시스템과 달리, StackItUp은 대략적인 스케치에서 정확한 3D 블록 배치로의 간극을 메우는 추상적인 관계 그래프를 도입합니다. 이 그래프는 스케치의 노이즈가 많은 계량적 세부 정보는 무시하고 상징적인 기하학적 관계(예: 왼쪽에)와 안정성 패턴(예: 두 개의 기둥 다리)을 포착합니다. 그런 다음 구성 확산 모델을 사용하여 이 그래프를 3D 자세로 기반을 두고, 스케치에는 없지만 안정성에 중요한 숨겨진 내부 및 후면 지지대를 예측하여 반복적으로 업데이트합니다. 상징적인 랜드마크와 현대식 주택 디자인의 스케치에 대한 평가에서 StackItUp은 일관되게 안정적인 다층 3D 구조를 생성하며 안정성과 시각적 유사성 모두에서 모든 기준선을 능가합니다.

시사점, 한계점

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시사점:

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2D 스케치만으로 복잡한 3D 구조를 생성 가능하게 함으로써 로봇 조작의 접근성을 크게 향상시킵니다.

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구성 확산 모델과 추상 관계 그래프를 활용하여 스케치의 부정확성을 효과적으로 처리합니다.

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안정적인 다층 3D 구조 생성을 통해 실제 로봇 조작 응용 분야에 적용 가능성을 높입니다.

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비전문가도 쉽게 사용할 수 있는 직관적인 인터페이스를 제공합니다.

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한계점:

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스케치의 해석 정확도는 스케치의 질에 의존할 수 있습니다. (스케치가 매우 부정확할 경우 정확한 3D 모델 생성이 어려울 수 있습니다.)

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현재는 블록 형태의 물체만을 다루므로, 다양한 형태의 물체를 다루는 데에는 추가적인 연구가 필요합니다.

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실제 로봇 시스템과의 통합 및 실제 환경에서의 성능 검증이 추가적으로 필요합니다.

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다양한 스타일의 스케치에 대한 일반화 성능 평가가 필요합니다.

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