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

CLASP: Cross-modal Salient Anchor-based Semantic Propagation for Weakly-supervised Dense Audio-Visual Event Localization

Created by

Haebom

저자

Jinxing Zhou, Ziheng Zhou, Yanghao Zhou, Yuxin Mao, Zhangling Duan, Dan Guo

개요

본 논문은 약하게 지도되는 설정(W-DAVEL task) 하에서 밀집 오디오-비주얼 이벤트 위치 확인(DAVEL) 문제를 다룹니다. W-DAVEL은 비디오 수준의 이벤트 레이블만 제공되고 각 이벤트의 시간적 경계가 알려지지 않은 더욱 어려운 설정입니다. 이를 해결하기 위해, 오디오 및 비주얼 모달리티에서 높은 일관성을 보이는 신뢰할 수 있는 타임스탬프인 '교차 모달 두드러진 앵커(cross-modal salient anchors)'를 활용합니다. 구체적으로, 예측된 오디오 및 비주얼 이벤트 클래스 간의 불일치를 측정하여 일치 점수를 생성하는 '상호 이벤트 일치 평가(Mutual Event Agreement Evaluation)' 모듈을 제안합니다. 이 일치 점수는 전역 비디오 및 지역 시간 창 식별 메커니즘을 통해 오디오 및 비주얼 앵커 특징을 식별하는 '교차 모달 두드러진 앵커 식별(Cross-modal Salient Anchor Identification)' 모듈에 사용됩니다. 다중 모달 통합 후의 앵커 특징은 '앵커 기반 시간 전파(Anchor-based Temporal Propagation)' 모듈에 공급되어 원래 시간적 오디오 및 비주얼 특징에서 이벤트 의미론적 인코딩을 향상시키고, 약하게 지도되는 환경에서 더 나은 시간적 위치 확인을 가능하게 합니다. UnAV-100 및 ActivityNet1.3 데이터셋에 대한 W-DAVEL 벤치마크를 구축하고, 광범위한 실험을 통해 최첨단 성능을 달성함을 보여줍니다.

시사점, 한계점

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시사점:

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약하게 지도되는 설정에서의 DAVEL 문제에 대한 새로운 접근 방식 제시

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교차 모달 두드러진 앵커를 활용한 효과적인 weakly-supervised event localization 방법 제안

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UnAV-100 및 ActivityNet1.3 데이터셋에서 최첨단 성능 달성

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W-DAVEL task에 대한 새로운 벤치마크 구축

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한계점:

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제안된 방법의 일반화 성능에 대한 추가적인 연구 필요

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다양한 유형의 오디오-비주얼 데이터에 대한 로버스트성 평가 필요

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더욱 복잡하고 다양한 이벤트가 포함된 데이터셋에 대한 성능 평가 필요

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