Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
본 페이지는 Google Gemini를 활용해 요약 정리하며, 비영리로 운영 됩니다.
논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

AI4Research: A Survey of Artificial Intelligence for Scientific Research

Towards Foundation Auto-Encoders for Time-Series Anomaly Detection

Bridging UI Design and chatbot Interactions: Applying Form-Based Principles to Conversational Agents

mGRADE: Minimal Recurrent Gating Meets Delay Convolutions for Lightweight Sequence Modeling

MILP-SAT-GNN: Yet Another Neural SAT Solver

Empowering Manufacturers with Privacy-Preserving AI Tools: A Case Study in Privacy-Preserving Machine Learning to Solve Real-World Problems

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs

How Do Vision-Language Models Process Conflicting Information Across Modalities?

Are Vision Transformer Representations Semantically Meaningful? A Case Study in Medical Imaging

Probing Evaluation Awareness of Language Models

MuRating: A High Quality Data Selecting Approach to Multilingual Large Language Model Pretraining

BranchNet: A Neuro-Symbolic Learning Framework for Structured Multi-Class Classification

GPU-based complete search for nonlinear minimization subject to bounds

Enhanced Generative Model Evaluation with Clipped Density and Coverage

Tuning without Peeking: Provable Privacy and Generalization Bounds for LLM Post-Training

ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving

Towards culturally-appropriate conversational AI for health in the majority world: An exploratory study with citizens and professionals in Latin America

AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness

Exploring Advanced LLM Multi-Agent Systems Based on Blackboard Architecture

Relational Causal Discovery with Latent Confounders

GPT, But Backwards: Exactly Inverting Language Model Outputs

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling

Deep Recommender Models Inference: Automatic Asymmetric Data Flow Optimization

Comparing Optimization Algorithms Through the Lens of Search Behavior Analysis

AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training

Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective

GradMetaNet: An Equivariant Architecture for Learning on Gradients

Customized Exploration of Landscape Features Driving Multi-Objective Combinatorial Optimization Performance

Depth Anything at Any Condition

Tile and Slide : A New Framework for Scaling NeRF from Local to Global 3D Earth Observation

Prompt Guidance and Human Proximal Perception for HOT Prediction with Regional Joint Loss

Enhanced Influence-aware Group Recommendation for Online Media Propagation

Survivability of Backdoor Attacks on Unconstrained Face Recognition Systems

Data Agent: A Holistic Architecture for Orchestrating Data+AI Ecosystems

Autonomous AI Surveillance: Multimodal Deep Learning for Cognitive and Behavioral Monitoring

Exploring Classical Piano Performance Generation with Expressive Music Variational AutoEncoder

Real-Time Emergency Vehicle Siren Detection with Efficient CNNs on Embedded Hardware

Self-Guided Process Reward Optimization with Masked Step Advantage for Process Reinforcement Learning

Crafting Hanzi as Narrative Bridges: An AI Co-Creation Workshop for Elderly Migrants

AI and Remote Sensing for Resilient and Sustainable Built Environments: A Review of Current Methods, Open Data and Future Directions

Chargax: A JAX Accelerated EV Charging Simulator

Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence

Integrating Traditional and Deep Learning Methods to Detect Tree Crowns in Satellite Images

Crop Pest Classification Using Deep Learning Techniques: A Review

BioMARS: A Multi-Agent Robotic System for Autonomous Biological Experiments

Epistemic Scarcity: The Economics of Unresolvable Unknowns

Evaluating the Effectiveness of Direct Preference Optimization for Personalizing German Automatic Text Simplifications for Persons with Intellectual Disabilities

Zero-Incentive Dynamics: a look at reward sparsity through the lens of unrewarded subgoals

NOCTIS: Novel Object Cyclic Threshold based Instance Segmentation

Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0

Tensor Program Optimization for the RISC-V Vector Extension Using Probabilistic Programs

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices

Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems

DocShaDiffusion: Diffusion Model in Latent Space for Document Image Shadow Removal

Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing

Evaluating LLM Agent Collusion in Double Auctions

Age Sensitive Hippocampal Functional Connectivity: New Insights from 3D CNNs and Saliency Mapping

Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound

Distributional Soft Actor-Critic with Diffusion Policy

RALLY: Role-Adaptive LLM-Driven Yoked Navigation for Agentic UAV Swarms

Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy

User-guided Generative Source Separation

LEDOM: An Open and Fundamental Reverse Language Model

Reasoner for Real-World Event Detection: Scaling Reinforcement Learning via Adaptive Perplexity-Aware Sampling Strategy

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks

Neural Hamiltonian Operator

VLAD: A VLM-Augmented Autonomous Driving Framework with Hierarchical Planning and Interpretable Decision Process

Rethinking All Evidence: Enhancing Trustworthy Retrieval-Augmented Generation via Conflict-Driven Summarization

AI Meets Maritime Training: Precision Analytics for Enhanced Safety and Performance

PULSE: Practical Evaluation Scenarios for Large Multimodal Model Unlearning

LLM-based Realistic Safety-Critical Driving Video Generation

GAIus: Combining Genai with Legal Clauses Retrieval for Knowledge-based Assistant

Beyond First-Order: Training LLMs with Stochastic Conjugate Subgradients and AdamW

Capacity Planning and Scheduling for Jobs with Uncertainty in Resource Usage and Duration

Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives

Are Large Brainwave Foundation Models Capable Yet? Insights from Fine-tuning

Geometry-aware 4D Video Generation for Robot Manipulation

AI-guided digital intervention with physiological monitoring reduces intrusive memories after experimental trauma

Empirical Analysis Of Heuristic and Approximation Algorithms for the The Mutual-Visibility Problem

Evaluation of a Foundational Model and Stochastic Models for Forecasting Sporadic or Spiky Production Outages of High-Performance Machine Learning Services

FAIR-MATCH: A Multi-Objective Framework for Bias Mitigation in Reciprocal Dating Recommendations

Quantifying Student Success with Generative AI: A Monte Carlo Simulation Informed by Systematic Review

Epitome: Pioneering an Experimental Platform for AI-Social Science Integration

Automated Vehicles Should be Connected with Natural Language

A Data Science Approach to Calcutta High Court Judgments: An Efficient LLM and RAG-powered Framework for Summarization and Similar Cases Retrieval

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey

XxaCT-NN: Structure Agnostic Multimodal Learning for Materials Science

Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

Long-Sequence Memory with Temporal Kernels and Dense Hopfield Functionals

Can AI be Consentful?

Text Detoxification: Data Efficiency, Semantic Preservation and Model Generalization

Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals

Data Classification with Dynamically Growing and Shrinking Neural Networks

Can Argus Judge Them All? Comparing VLMs Across Domains

Fast AI Model Splitting over Edge Networks

Fast Clifford Neural Layers

On-Policy Optimization of ANFIS Policies Using Proximal Policy Optimization

Learning to Segment for Vehicle Routing Problems

Systemic Constraints of Undecidability

Research on Low-Latency Inference and Training Efficiency Optimization for Graph Neural Network and Large Language Model-Based Recommendation Systems

AudioTrust: Benchmarking the Multifaceted Trustworthiness of Audio Large Language Models

Created by

Haebom

저자

Kai Li, Can Shen, Yile Liu, Jirui Han, Kelong Zheng, Xuechao Zou, Zhe Wang, Xingjian Du, Shun Zhang, Hanjun Luo, Yingbin Jin, Xinxin Xing, Ziyang Ma, Yue Liu, Xiaojun Jia, Yifan Zhang, Junfeng Fang, Kun Wang, Yibo Yan, Haoyang Li, Yiming Li, Xiaobin Zhuang, Yang Liu, Haibo Hu, Zhizheng Wu, Xiaolin Hu, Eng-Siong Chng, XiaoFeng Wang, Wenyuan Xu, Wei Dong, Xinfeng Li

개요

본 논문은 오디오 대규모 언어 모델(ALLM)의 신뢰성 평가를 위한 최초의 다면적 신뢰성 평가 프레임워크이자 벤치마크인 AudioTrust를 제시한다. 기존 평가 프레임워크는 텍스트 모달리티에 중점을 두거나 제한적인 안전 측면만 다루는 한계가 있었으나, AudioTrust는 공정성, 환각, 안전성, 프라이버시, 견고성, 인증 등 6가지 주요 측면에 걸쳐 ALLM을 평가한다. 실제 시나리오(일상 대화, 응급 전화, 음성 비서 상호작용 등)에서 수집한 4,420개 이상의 오디오/텍스트 샘플로 구성된 데이터셋과 9개의 오디오 특화 평가 지표를 사용하여 18가지 실험 설정을 통해 ALLM의 신뢰성을 종합적으로 평가한다. 실험 결과는 다양한 고위험 오디오 시나리오에서 최첨단 오픈소스 및 클로즈드소스 ALLM의 신뢰성 한계를 보여주며, 향후 오디오 모델의 안전하고 신뢰할 수 있는 배포를 위한 귀중한 통찰력을 제공한다. AudioTrust 플랫폼과 벤치마크는 GitHub에서 공개된다.

시사점, 한계점

•

시사점:

◦

오디오 모달리티의 고유한 특성과 응용 시나리오를 고려한 최초의 ALLM 신뢰성 평가 프레임워크 및 벤치마크 제시.

◦

6가지 주요 측면(공정성, 환각, 안전성, 프라이버시, 견고성, 인증)에 대한 포괄적인 평가 제공.

◦

실제 시나리오 기반의 대규모 데이터셋과 오디오 특화 평가 지표를 활용한 객관적이고 확장 가능한 평가.

◦

최첨단 ALLM의 신뢰성 한계를 밝히고 향후 모델 개발 및 배포에 대한 중요한 시사점 제시.

◦

오픈소스를 통해 연구 공유 및 재현성 확보.

•

한계점:

◦

본 연구에서 제시된 데이터셋과 평가 지표가 모든 유형의 ALLM과 모든 가능한 위험 시나리오를 포괄하지 못할 수 있음.

◦

평가 결과는 사용된 특정 데이터셋과 평가 지표에 의존적일 수 있으므로, 다른 데이터셋이나 지표를 사용할 경우 결과가 달라질 수 있음.

◦

새로운 ALLM 아키텍처 및 응용 프로그램의 등장에 따라 프레임워크의 지속적인 업데이트 및 개선이 필요함.

Made with Slashpage