Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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Structure Transfer: an Inference-Based Calculus for the Transformation of Representations

Ensemble of Pathology Foundation Models for MIDOG 2025 Track 2: Atypical Mitosis Classification

AudioCodecBench: A Comprehensive Benchmark for Audio Codec Evaluation

Understanding Space Is Rocket Science -- Only Top Reasoning Models Can Solve Spatial Understanding Tasks

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression

Modular Techniques for Synthetic Long-Context Data Generation in Language Model Training and Evaluation

EZhouNet:A framework based on graph neural network and anchor interval for the respiratory sound event detection

AImoclips: A Benchmark for Evaluating Emotion Conveyance in Text-to-Music Generation

First Order Model-Based RL through Decoupled Backpropagation

Pilot Study on Generative AI and Critical Thinking in Higher Education Classrooms

Beacon: Post-Training Quantization with Integrated Grid Selection

Is Artificial Intelligence Reshaping the Landscape of the International Academic Community of Geosciences?

Vectorized Attention with Learnable Encoding for Quantum Transformer

Transplant Then Regenerate: A New Paradigm for Text Data Augmentation

Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration

MultiGen: Child-Friendly Multilingual Speech Generator with LLMs

StreetViewAI: Making Street View Accessible Using Context-Aware Multimodal AI

Street-Level AI: Are Large Language Models Ready for Real-World Judgments?

The KG-ER Conceptual Schema Language

LOTS of Fashion! Multi-Conditioning for Image Generation via Sketch-Text Pairing

Conditional Video Generation for High-Efficiency Video Compression

TriCLIP-3D: A Unified Parameter-Efficient Framework for Tri-Modal 3D Visual Grounding based on CLIP

Demographic-aware fine-grained classification of pediatric wrist fractures

An Analysis of Action-Value Temporal-Difference Methods That Learn State Values

Stochastic Parameter Decomposition

Auto-Regressive vs Flow-Matching: a Comparative Study of Modeling Paradigms for Text-to-Music Generation

MiniCPM4: Ultra-Efficient LLMs on End Devices

Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling

How Can I Publish My LLM Benchmark Without Giving the True Answers Away?

Optimization of Module Transferability in Single Image Super-Resolution: Universality Assessment and Cycle Residual Blocks

Transferable Mask Transformer: Cross-domain Semantic Segmentation with Region-adaptive Transferability Estimation

RBT4DNN: Requirements-based Testing of Neural Networks

Robust Offline Imitation Learning Through State-level Trajectory Stitching

Beyond holography: the entropic quantum gravity foundations of image processing

KNighter: Transforming Static Analysis with LLM-Synthesized Checkers

FRIDA to the Rescue! Analyzing Synthetic Data Effectiveness in Object-Based Common Sense Reasoning for Disaster Response

CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection

Rapid Word Learning Through Meta In-Context Learning

Image Embedding Sampling Method for Diverse Captioning

Is an Ultra Large Natural Image-Based Foundation Model Superior to a Retina-Specific Model for Detecting Ocular and Systemic Diseases?

Extended Histogram-based Outlier Score (EHBOS)

A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models

Breaking the Context Bottleneck on Long Time Series Forecasting

Defending LVLMs Against Vision Attacks through Partial-Perception Supervision

ACING: Actor-Critic for Instruction Learning in Black-Box LLMs

Kolb-Based Experiential Learning for Generalist Agents with Human-Level Kaggle Data Science Performance

Quantifying Calibration Error in Neural Networks Through Evidence-Based Theory

Robust training of implicit generative models for multivariate and heavy-tailed distributions with an invariant statistical loss

Learning from 10 Demos: Generalisable and Sample-Efficient Policy Learning with Oriented Affordance Frames

AutoPETIII: The Tracer Frontier. What Frontier?

Long Input Sequence Network for Long Time Series Forecasting

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

Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers

MTP: A Meaning-Typed Language Abstraction for AI-Integrated Programming

Diffusion on language model encodings for protein sequence generation

Style Transfer to Calvin and Hobbes comics using Stable Diffusion

Autonomation, Not Automation: Activities and Needs of European Fact-checkers as a Basis for Designing Human-Centered AI Systems

Plan Verification for LLM-Based Embodied Task Completion Agents

EigenBench: A Comparative Behavioral Measure of Value Alignment

Oyster-I: Beyond Refusal -- Constructive Safety Alignment for Responsible Language Models

Extending FKG.in: Towards a Food Claim Traceability Network

DeepVIS: Bridging Natural Language and Data Visualization Through Step-wise Reasoning

Theory of Mind Using Active Inference: A Framework for Multi-Agent Cooperation

CP-Bench: Evaluating Large Language Models for Constraint Modelling

Axiomatics of Restricted Choices by Linear Orders of Sets with Minimum as Fallback

DMN-Guided Prompting: A Framework for Controlling LLM Behavior

Computational Basis of LLM's Decision Making in Social Simulation

Science Across Languages: Assessing LLM Multilingual Translation of Scientific Papers

Enhancing FKG.in: automating Indian food composition analysis

WASP: A Weight-Space Approach to Detecting Learned Spuriousness

Transferable Belief Model on Quantum Circuits

PIN: A Knowledge-Intensive Dataset for Paired and Interleaved Multimodal Documents

(Ir)rationality in AI: State of the Art, Research Challenges and Open Questions

Intelligence Primer

ChronoGraph: A Real-World Graph-Based Multivariate Time Series Dataset

Delta Activations: A Representation for Finetuned Large Language Models

DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation

Towards a Unified View of Large Language Model Post-Training

No Thoughts Just AI: Biased LLM Recommendations Limit Human Agency in Resume Screening

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

SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer

Parking Availability Prediction via Fusing Multi-Source Data with A Self-Supervised Learning Enhanced Spatio-Temporal Inverted Transformer

PARCO: Phoneme-Augmented Robust Contextual ASR via Contrastive Entity Disambiguation

AUDETER: A Large-scale Dataset for Deepfake Audio Detection in Open Worlds

From Editor to Dense Geometry Estimator

Decoupled Entity Representation Learning for Pinterest Ads Ranking

Facts Fade Fast: Evaluating Memorization of Outdated Medical Knowledge in Large Language Models

HumAIne-Chatbot: Real-Time Personalized Conversational AI via Reinforcement Learning

Reinforcement Learning for Robust Ageing-Aware Control of Li-ion Battery Systems with Data-Driven Formal Verification

An Empirical Study of Vulnerabilities in Python Packages and Their Detection

How many patients could we save with LLM priors?

Learning Active Perception via Self-Evolving Preference Optimization for GUI Grounding

MAGneT: Coordinated Multi-Agent Generation of Synthetic Multi-Turn Mental Health Counseling Sessions

VisioFirm: Cross-Platform AI-assisted Annotation Tool for Computer Vision

Crossing the Species Divide: Transfer Learning from Speech to Animal Sounds

YOLO Ensemble for UAV-based Multispectral Defect Detection in Wind Turbine Components

Attention as an Adaptive Filter

TAGAL: Tabular Data Generation using Agentic LLM Methods

Enhancing Technical Documents Retrieval for RAG

AImoclips: A Benchmark for Evaluating Emotion Conveyance in Text-to-Music Generation

Created by

Haebom

저자

Gyehun Go, Satbyul Han, Ahyeon Choi, Eunjin Choi, Juhan Nam, Jeong Mi Park

개요

본 논문은 텍스트를 음악으로 변환하는 시스템(TTM)의 감정 표현 능력을 평가하기 위한 벤치마크인 AImoclips를 제시합니다. 12가지 감정 의도를 바탕으로 6개의 최첨단 TTM 시스템을 사용하여 1,000개 이상의 음악 클립을 생성하고, 111명의 참가자에게 각 클립의 valence와 arousal을 9점 Likert 척도로 평가하게 했습니다. 실험 결과, 상용 시스템은 의도보다 더 쾌적한 음악을 생성하는 경향이 있고, 오픈소스 시스템은 그 반대 경향을 보였습니다. 모든 시스템에서 고각성 상태일 때 감정이 더 정확하게 전달되었으며, 모든 시스템이 감정적 중립성에 치우치는 편향을 보였습니다. AImoclips는 모델별 감정 표현 특성에 대한 통찰력을 제공하고 감정적으로 일치하는 TTM 시스템의 미래 개발을 지원합니다.

시사점, 한계점

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시사점:

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TTM 시스템의 감정 표현 능력에 대한 정량적 평가 기준 마련 (AImoclips 벤치마크)

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상용 및 오픈소스 TTM 시스템의 감정 표현 특성 비교 분석 (상용 시스템은 더 쾌적하게, 오픈소스 시스템은 의도와 반대로 생성하는 경향)

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고각성 상태에서 감정 전달이 더 효과적임을 밝힘

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TTM 시스템의 감정적 중립성 편향을 확인

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한계점:

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AImoclips 벤치마크가 특정 감정 및 모델에 국한될 수 있음

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valence와 arousal만을 사용하여 감정을 평가하여 감정의 다양성을 충분히 반영하지 못할 수 있음

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참가자 수가 제한적일 수 있음 (111명)

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감정적 중립성 편향의 원인 및 해결 방안에 대한 추가 연구 필요

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