Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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Benchmarking LLM Causal Reasoning with Scientifically Validated Relationships

TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics

Mining the Mind: What 100M Beliefs Reveal About Frontier LLM Knowledge

Open ASR Leaderboard: Towards Reproducible and Transparent Multilingual and Long-Form Speech Recognition Evaluation

Emotionally Vulnerable Subtype of Internet Gaming Disorder: Measuring and Exploring the Pathology of Problematic Generative AI Use

Explaining raw data complexity to improve satellite onboard processing

Foundations of LLM Knowledge Materialization: Termination, Reproducibility, Robustness

Incremental Summarization for Customer Support via Progressive Note-Taking and Agent Feedback

SDAR: A Synergistic Diffusion-AutoRegression Paradigm for Scalable Sequence Generation

A Multimodal GUI Architecture for Interfacing with LLM-Based Conversational Assistants

Distributional Semantics Tracing: A Framework for Explaining Hallucinations in Large Language Models

DACP: Domain-Adaptive Continual Pre-Training of Large Language Models for Phone Conversation Summarization

High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training

Provable Speech Attributes Conversion via Latent Independence

Chronological Thinking in Full-Duplex Spoken Dialogue Language Models

Paper2Video: Automatic Video Generation from Scientific Papers

MacroBench: A Novel Testbed for Web Automation Scripts via Large Language Models

Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models

Generalized Orders of Magnitude for Scalable, Parallel, High-Dynamic-Range Computation

LogAction: Consistent Cross-system Anomaly Detection through Logs via Active Domain Adaptation

Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models

More Than One Teacher: Adaptive Multi-Guidance Policy Optimization for Diverse Exploration

Learning to Reason for Hallucination Span Detection

Panorama: Fast-Track Nearest Neighbors

Feature Identification via the Empirical NTK

OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction

Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning

Real-time Noise Detection and Classification in Single-Channel EEG: A Lightweight Machine Learning Approach for EMG, White Noise, and EOG Artifacts

The Sandbox Configurator: A Framework to Support Technical Assessment in AI Regulatory Sandboxes

CORE-3D: Context-aware Open-vocabulary Retrieval by Embeddings in 3D

PARL-MT: Learning to Call Functions in Multi-Turn Conversation with Progress Awareness

Defending MoE LLMs against Harmful Fine-Tuning via Safety Routing Alignment

Learn the Ropes, Then Trust the Wins: Self-imitation with Progressive Exploration for Agentic Reinforcement Learning

InfiR2: A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models

MORPH: Shape-agnostic PDE Foundation Models

Spiffy: Multiplying Diffusion LLM Acceleration via Lossless Speculative Decoding

Evaluating LLM-Generated Versus Human-Authored Responses in Role-Play Dialogues

Audio-Conditioned Diffusion LLMs for ASR and Deliberation Processing

Hierarchical Reinforcement Learning with Low-Level MPC for Multi-Agent Control

ProtoMedX: Towards Explainable Multi-Modal Prototype Learning for Bone Health Classification

From Correction to Mastery: Reinforced Distillation of Large Language Model Agents

Reproducible workflow for online AI in digital health

HiChunk: Evaluating and Enhancing Retrieval-Augmented Generation with Hierarchical Chunking

FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification

TalkPlayData 2: An Agentic Synthetic Data Pipeline for Multimodal Conversational Music Recommendation

A Survey of Reinforcement Learning for Large Reasoning Models

X-Teaming Evolutionary M2S: Automated Discovery of Multi-turn to Single-turn Jailbreak Templates

Barycentric Neural Networks and Length-Weighted Persistent Entropy Loss: A Green Geometric and Topological Framework for Function Approximation

Scaling Performance of Large Language Model Pretraining

Towards Methane Detection Onboard Satellites

AEGIS : Automated Co-Evolutionary Framework for Guarding Prompt Injections Schema

Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning

Safe-Control: A Safety Patch for Mitigating Unsafe Content in Text-to-Image Generation Models

Condition Weaving Meets Expert Modulation: Towards Universal and Controllable Image Generation

Long Chain-of-Thought Reasoning Across Languages

MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging

MCPSecBench: A Systematic Security Benchmark and Playground for Testing Model Context Protocols

MInDI-3D: Iterative Deep Learning in 3D for Sparse-view Cone Beam Computed Tomography

MAViS: A Multi-Agent Framework for Long-Sequence Video Storytelling

CoCoA: Collaborative Chain-of-Agents for Parametric-Retrieved Knowledge Synergy

Can Small-Scale Data Poisoning Exacerbate Dialect-Linked Biases in Large Language Models?

Distilling a Small Utility-Based Passage Selector to Enhance Retrieval-Augmented Generation

From Feedback to Checklists: Grounded Evaluation of AI-Generated Clinical Notes

Controllable Hybrid Captioner for Improved Long-form Video Understanding

Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks

Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives

ERR@HRI 2.0 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Conversations

Efficiency-Effectiveness Reranking FLOPs for LLM-based Rerankers

Truth, Trust, and Trouble: Medical AI on the Edge

LLMs on a Budget? Say HOLA

The Role of Model Confidence on Bias Effects in Measured Uncertainties for Vision-Language Models

A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysis

Breaking the Reviewer: Assessing the Vulnerability of Large Language Models in Automated Peer Review Under Textual Adversarial Attacks

Not All Clients Are Equal: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients

Rethinking Losses for Diffusion Bridge Samplers

Think With Videos For Agentic Long-Video Understanding

ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning

Intention-Conditioned Flow Occupancy Models

Product of Experts for Visual Generation

Modality-Balancing Preference Optimization of Large Multimodal Models by Adversarial Negative Mining

Dissecting Logical Reasoning in LLMs: A Fine-Grained Evaluation and Supervision Study

Tug-of-war between idioms' figurative and literal interpretations in LLMs

MAGREF: Masked Guidance for Any-Reference Video Generation with Subject Disentanglement

GL-PGENet: A Parameterized Generation Framework for Robust Document Image Enhancement

CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation

Trans-EnV: A Framework for Evaluating the Linguistic Robustness of LLMs Against English Varieties

The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology

BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases

Inference-time Alignment in Continuous Space

STOPA: A Database of Systematic VariaTion Of DeePfake Audio for Open-Set Source Tracing and Attribution

Search Wisely: Mitigating Sub-optimal Agentic Searches By Reducing Uncertainty

Watch your steps: Dormant Adversarial Behaviors that Activate upon LLM Finetuning

LLINBO: Trustworthy LLM-in-the-Loop Bayesian Optimization

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation

Hakim: Farsi Text Embedding Model

Understanding In-context Learning of Addition via Activation Subspaces

Evaluating Evaluation Metrics -- The Mirage of Hallucination Detection

T-VEC: A Telecom-Specific Vectorization Model with Enhanced Semantic Understanding via Deep Triplet Loss Fine-Tuning

Hallucination Detection in LLMs with Topological Divergence on Attention Graphs

Provable Speech Attributes Conversion via Latent Independence

Created by

Haebom

저자

Jonathan Svirsky, Ofir Lindenbaum, Uri Shaham

개요

본 논문은 음성 변환 분야에서 데이터 속성 조작에 대한 강력한 제어와 해석 가능성을 제공하는 일반적인 프레임워크를 제안한다. 기존의 음성 스타일 변환 방식이 경험적인 것에 비해, 본 연구는 이론적 분석과 보장을 제공한다. 이 프레임워크는 비확률적 오토인코더 구조를 기반으로 하며, 예측된 잠재 변수와 제어 가능한 대상 변수 간의 독립성 제약 조건을 둔다. 이 설계를 통해 원본 콘텐츠를 보존하면서 관찰된 스타일 변수를 기반으로 일관된 신호 변환을 수행하고, 원하는 속성을 수정할 수 있다. 화자 정체성 및 감정과 같은 다양한 음성 스타일에 대한 실험을 통해 제안된 방법의 효과와 일반성을 입증한다.

시사점, 한계점

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시사점:

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음성 속성 변환을 위한 이론적 기반과 보장을 제공하는 프레임워크 제안.

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일관된 신호 변환을 가능하게 하여, 원본 콘텐츠 보존 및 원하는 속성 수정 가능.

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화자 정체성 및 감정과 같은 다양한 음성 스타일에 대한 효과적인 성능 입증.

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한계점:

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논문의 구체적인 이론적 분석 내용 및 가정에 대한 자세한 정보 부족.

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제안된 프레임워크의 일반화 가능성에 대한 추가적인 연구 필요.

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다른 데이터 유형 및 속성에 대한 적용 가능성 검증 필요.

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