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.

Sekai: A Video Dataset towards World Exploration

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction

One-Step Diffusion for Detail-Rich and Temporally Consistent Video Super-Resolution

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework

Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis

WebXAII: an open-source web framework to study human-XAI interaction

Refining music sample identification with a self-supervised graph neural network

Decoupled Classifier-Free Guidance for Counterfactual Diffusion Models

Essential-Web v1.0: 24T tokens of organized web data

Adaptive Guidance Accelerates Reinforcement Learning of Reasoning Models

LeVERB: Humanoid Whole-Body Control with Latent Vision-Language Instruction

Screen Hijack: Visual Poisoning of VLM Agents in Mobile Environments

SP-VLA: A Joint Model Scheduling and Token Pruning Approach for VLA Model Acceleration

Serving Large Language Models on Huawei CloudMatrix384

Machine Learning Methods for Small Data and Upstream Bioprocessing Applications: A Comprehensive Review

Med-U1: Incentivizing Unified Medical Reasoning in LLMs via Large-scale Reinforcement Learning

Two Heads Are Better than One: Simulating Large Transformers with Small Ones

BreastDCEDL: Curating a Comprehensive DCE-MRI Dataset and developing a Transformer Implementation for Breast Cancer Treatment Response Prediction

Semantic Preprocessing for LLM-based Malware Analysis

A Minimalist Method for Fine-tuning Text-to-Image Diffusion Models

Human-like Forgetting Curves in Deep Neural Networks

Convergent Linear Representations of Emergent Misalignment

LearnAlign: Reasoning Data Selection for Reinforcement Learning in Large Language Models Based on Improved Gradient Alignment

TARDIS STRIDE: A Spatio-Temporal Road Image Dataset and World Model for Autonomy

Autonomous Computer Vision Development with Agentic AI

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI

SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks

Using Language and Road Manuals to Inform Map Reconstruction for Autonomous Driving

Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing

PlantBert: An Open Source Language Model for Plant Science

Info-Coevolution: An Efficient Framework for Data Model Coevolution

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes

SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code

UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation

KVCache Cache in the Wild: Characterizing and Optimizing KVCache Cache at a Large Cloud Provider

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Towards Efficient Few-shot Graph Neural Architecture Search via Partitioning Gradient Contribution

Optimizing Sensory Neurons: Nonlinear Attention Mechanisms for Accelerated Convergence in Permutation-Invariant Neural Networks for Reinforcement Learning

CryoCCD: Conditional Cycle-consistent Diffusion with Biophysical Modeling for Cryo-EM Synthesis

More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement

Dynamic Risk Assessments for Offensive Cybersecurity Agents

SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation

Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets

Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression

Representation Learning with Mutual Influence of Modalities for Node Classification in Multi-Modal Heterogeneous Networks

Learning Dynamics in Continual Pre-Training for Large Language Models

Mask-PINNs: Regulating Feature Distributions in Physics-Informed Neural Networks

Assessing Tenstorrent's RISC-V MatMul Acceleration Capabilities

SPIN-ODE: Stiff Physics-Informed Neural ODE for Chemical Reaction Rate Estimation

PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding

DeepSelective: Interpretable Prognosis Prediction via Feature Selection and Compression in EHR Data

Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representations

AerialVG: A Challenging Benchmark for Aerial Visual Grounding by Exploring Positional Relations

PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization

TALE: A Tool-Augmented Framework for Reference-Free Evaluation of Large Language Models

Decentralized Collective World Model for Emergent Communication and Coordination

RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations

Efficient but Vulnerable: Benchmarking and Defending LLM Batch Prompting Attack

LLMs in Disease Diagnosis: A Comparative Study of DeepSeek-R1 and O3 Mini Across Chronic Health Conditions

Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies

QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation

Dynamic Knowledge Integration for Evidence-Driven Counter-Argument Generation with Large Language Models

AlignDistil: Token-Level Language Model Alignment as Adaptive Policy Distillation

Eau De $Q$-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning

Hierarchical and Modular Network on Non-prehensile Manipulation in General Environments

Selective Use of Yannakakis' Algorithm to Improve Query Performance: Machine Learning to the Rescue

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

Batayan: A Filipino NLP benchmark for evaluating Large Language Models

From RAG to Memory: Non-Parametric Continual Learning for Large Language Models

Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization

ShapeLib: Designing a library of programmatic 3D shape abstractions with Large Language Models

Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning

Guaranteed prediction sets for functional surrogate models

FDLLM: A Dedicated Detector for Black-Box LLMs Fingerprinting

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning

MonoSOWA: Scalable monocular 3D Object detector Without human Annotations

Representation Learning of Point Cloud Upsampling in Global and Local Inputs

Multi-Preference Optimization: Generalizing DPO via Set-Level Contrasts

Incivility and Rigidity: The Risks of Fine-Tuning LLMs for Political Argumentation

Song Form-aware Full-Song Text-to-Lyrics Generation with Multi-Level Granularity Syllable Count Control

Learning Multi-Branch Cooperation for Enhanced Click-Through Rate Prediction at Taobao

On the Limits of Language Generation: Trade-Offs Between Hallucination and Mode Collapse

Web Archives Metadata Generation with GPT-4o: Challenges and Insights

Cyclic Vision-Language Manipulator: Towards Reliable and Fine-Grained Image Interpretation for Automated Report Generation

A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning

Adapting While Learning: Grounding LLMs for Scientific Problems with Intelligent Tool Usage Adaptation

FALCON: Feedback-driven Adaptive Long/short-term memory reinforced Coding Optimization system

Efficient Mixture-of-Expert for Video-based Driver State and Physiological Multi-task Estimation in Conditional Autonomous Driving

ALTA: Compiler-Based Analysis of Transformers

Learning to Route LLMs with Confidence Tokens

Core Knowledge Deficits in Multi-Modal Language Models

AssistantX: An LLM-Powered Proactive Assistant in Collaborative Human-Populated Environment

MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension

Can Large Language Models Replace Human Subjects? A Large-Scale Replication of Scenario-Based Experiments in Psychology and Management

LogProber: Disentangling confidence from contamination in LLM responses

V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models

xGen-MM (BLIP-3): A Family of Open Large Multimodal Models

Understanding and Reducing the Class-Dependent Effects of Data Augmentation with A Two-Player Game Approach

PromptDSI: Prompt-based Rehearsal-free Instance-wise Incremental Learning for Document Retrieval

XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark

Created by

Haebom

저자

Ioan-Paul Ciobanu, Andrei-Iulian Hiji, Nicolae-Catalin Ristea, Paul Irofti, Cristian Rusu, Radu Tudor Ionescu

개요

본 논문은 최근 증가하는 오디오 딥페이크로 인한 위험성을 해결하기 위해, 다국어 지원 대규모 교차 도메인 오디오 딥페이크 벤치마크인 XMAD-Bench를 소개합니다. 기존 연구들이 주로 동일한 생성 모델로 훈련 및 테스트 데이터를 생성하는 도메인 내 설정에서 높은 정확도를 보고하는 것과 달리, XMAD-Bench는 화자, 생성 방법, 실제 오디오 소스가 훈련 및 테스트 데이터 간에 서로 다른 교차 도메인 설정을 제공합니다. 668.8시간 분량의 실제 및 딥페이크 음성 데이터를 포함하며, "실제 환경"에서 오디오 딥페이크 탐지기의 성능을 평가할 수 있도록 합니다. 실험 결과, 기존 탐지기들의 도메인 내 성능은 매우 높지만, 교차 도메인 성능은 우연에 가까울 정도로 낮다는 것을 보여주어, 다양한 언어, 화자, 생성 방법 및 데이터 소스에 대한 일반화 능력을 유지하는 강력한 오디오 딥페이크 탐지기 개발의 필요성을 강조합니다. XMAD-Bench는 https://github.com/ristea/xmad-bench/ 에서 공개됩니다.

GitHub - ristea/xmad-bench

Contribute to ristea/xmad-bench development by creating an account on GitHub.

시사점, 한계점

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시사점:

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기존 오디오 딥페이크 탐지기의 도메인 내 성능과 교차 도메인 성능 간의 큰 차이를 밝혀냄으로써, 현존 기술의 한계를 명확히 제시합니다.

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다양한 상황에서 일반화 가능한 강건한 오디오 딥페이크 탐지기 개발의 중요성을 강조합니다.

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대규모 다국어 교차 도메인 오디오 딥페이크 벤치마크 XMAD-Bench를 공개하여, 향후 연구의 발전에 기여합니다.

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한계점:

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XMAD-Bench가 모든 가능한 오디오 딥페이크 생성 방법과 데이터 소스를 포함하지는 않을 수 있습니다. 따라서, 실제 세계의 모든 시나리오를 완벽하게 반영하지 못할 수 있습니다.

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벤치마크의 성능 평가는 특정 지표에 의존하므로, 다양한 평가 지표를 활용한 추가적인 분석이 필요할 수 있습니다.

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