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

InstructAudio: Unified speech and music generation with natural language instruction

Created by

Haebom

Category

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저자

Chunyu Qiang, Kang Yin, Xiaopeng Wang, Yuzhe Liang, Jiahui Zhao, Ruibo Fu, Tianrui Wang, Cheng Gong, Chen Zhang, Longbiao Wang, Jianwu Dang

개요

InstructAudio는 음성 및 음악 생성에 대한 지침 기반 (자연어 설명) 제어를 가능하게 하는 통합 프레임워크입니다. 음성, 음악, 대화 생성에 대해 억양(성별, 나이), 부가언어(감정, 스타일, 억양) 및 음악적(장르, 악기, 리듬, 분위기) 특성을 제어할 수 있습니다. 50K 시간의 음성 데이터와 20K 시간의 음악 데이터를 사용하여 훈련된 이 모델은 표준화된 지침-음소 입력 형식을 사용하며, 다중 작업 학습 및 교차 모달 정렬을 지원합니다. InstructAudio는 주류 TTS 및 TTM 모델과 비교하여 대부분의 메트릭에서 최적의 결과를 달성했습니다.

시사점, 한계점

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음성 및 음악 생성을 위한 최초의 지침 제어 통합 프레임워크입니다.

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억양, 부가언어 및 음악적 특성을 자연어 지침으로 제어할 수 있습니다.

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영어 및 중국어로 표현력 있는 음성, 음악 및 대화 생성을 지원합니다.

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다중 작업 학습 및 교차 모달 정렬을 가능하게 합니다.

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50K 시간의 음성 및 20K 시간의 음악 데이터로 훈련되었습니다.

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한계점은 구체적으로 명시되지 않았습니다.

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