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Daily Arxiv

世界中で発行される人工知能関連の論文をまとめるページです。
このページはGoogle Geminiを活用して要約し、非営利で運営しています。
論文の著作権は著者および関連機関にあり、共有する際は出典を明記してください。

Merge Kernel for Bayesian Optimization on Permutation Space

Demographic-aware fine-grained classification of pediatric wrist fractures

Generative Multi-Target Cross-Domain Recommendation

ParaStudent: Generating and Evaluating Realistic Student Code by Teaching LLMs to Struggle

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models

EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos

Inversion-DPO: Precise and Efficient Post-Training for Diffusion Models

A Simple Baseline for Stable and Plastic Neural Networks

WildFX: A DAW-Powered Pipeline for In-the-Wild Audio FX Graph Modeling

From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation

Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

How Not to Detect Prompt Injections with an LLM

Critiques of World Models

The role of large language models in UI/UX design: A systematic literature review

LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop

STACK: Adversarial Attacks on LLM Safeguard Pipelines

ZonUI-3B: A Lightweight Vision-Language Model for Cross-Resolution GUI Grounding

Understanding Reasoning in Thinking Language Models via Steering Vectors

Agentic Neural Networks: Self-Evolving Multi-Agent Systems via Textual Backpropagation

EvolveNav: Self-Improving Embodied Reasoning for LLM-Based Vision-Language Navigation

TextDiffuser-RL: Efficient and Robust Text Layout Optimization for High-Fidelity Text-to-Image Synthesis

SpecMaskFoley: Steering Pretrained Spectral Masked Generative Transformer Toward Synchronized Video-to-audio Synthesis via ControlNet

Exploring Graph Representations of Logical Forms for Language Modeling

DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs

CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors

Hands-On: Segmenting Individual Signs from Continuous Sequences

Can we ease the Injectivity Bottleneck on Lorentzian Manifolds for Graph Neural Networks?

Align Your Rhythm: Generating Highly Aligned Dance Poses with Gating-Enhanced Rhythm-Aware Feature Representation

HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results

An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model

Evaluating link prediction: New perspectives and recommendations

Learning to Reason at the Frontier of Learnability

Stonefish: Supporting Machine Learning Research in Marine Robotics

Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning

On the Transfer of Knowledge in Quantum Algorithms

Code Readability in the Age of Large Language Models: An Industrial Case Study from Atlassian

Bias in Decision-Making for AI's Ethical Dilemmas: A Comparative Study of ChatGPT and Claude

ASTRID - An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems

Consistency of Responses and Continuations Generated by Large Language Models on Social Media

From Code to Compliance: Assessing ChatGPT's Utility in Designing an Accessible Webpage -- A Case Study

Temporal reasoning for timeline summarisation in social media

Invisible Textual Backdoor Attacks based on Dual-Trigger

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models

Two-Stage Pretraining for Molecular Property Prediction in the Wild

Towards Practical Operation of Deep Reinforcement Learning Agents in Real-World Network Management at Open RAN Edges

An Approach for Auto Generation of Labeling Functions for Software Engineering Chatbots

Bridging Local and Global Knowledge via Transformer in Board Games

Entropy Loss: An Interpretability Amplifier of 3D Object Detection Network for Intelligent Driving

FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image Translation

On Pre-training of Multimodal Language Models Customized for Chart Understanding

Visual Grounding Methods for Efficient Interaction with Desktop Graphical User Interfaces

Instruct-MusicGen: Unlocking Text-to-Music Editing for Music Language Models via Instruction Tuning

Meta4XNLI: A Crosslingual Parallel Corpus for Metaphor Detection and Interpretation

SecurePose: Automated Face Blurring and Human Movement Kinematics Extraction from Videos Recorded in Clinical Settings

Improved DDIM Sampling with Moment Matching Gaussian Mixtures

Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges

From Roots to Rewards: Dynamic Tree Reasoning with RL

Illuminating the Three Dogmas of Reinforcement Learning under Evolutionary Light

Instance space analysis of the capacitated vehicle routing problem

Multi-Agent LLMs as Ethics Advocates for AI-Based Systems

GATSim: Urban Mobility Simulation with Generative Agents

Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

Strategic Reflectivism In Intelligent Systems

SafeAgent: Safeguarding LLM Agents via an Automated Risk Simulator

What the F*ck Is Artificial General Intelligence?

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios

To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization

BLAST: A Stealthy Backdoor Leverage Attack against Cooperative Multi-Agent Deep Reinforcement Learning based Systems

UniEmoX: Cross-modal Semantic-Guided Large-Scale Pretraining for Universal Scene Emotion Perception

CorMulT: A Semi-supervised Modality Correlation-aware Multimodal Transformer for Sentiment Analysis

Toward Temporal Causal Representation Learning with Tensor Decomposition

Kolmogorov Arnold Networks (KANs) for Imbalanced Data - An Empirical Perspective

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining

Lessons from the TREC Plain Language Adaptation of Biomedical Abstracts (PLABA) トラック

Multi-Centre Validation of a Deep Learning Model for Scoliosis Assessment

The Emotion-Memory Link: Do Memorability Annotations Matter for Intelligent Systems?

DENSE: Longitudinal Progress Note Generation with Temporal Modeling of Heterogeneous Clinical Notes Across Hospital Visits

Edge Intelligence with Spiking Neural Networks

VLA-Mark: A cross modal watermark for large vision-language alignment model

Noradrenergic-inspired gain modulation attenuates the stability gap in joint training

A multi-strategy improved snake optimizer for 3-dimensional UAV path planning and engineering problems

Photonic Fabric Platform for AI Accelerators

OrthoInsight: Rib Fracture Diagnosis and Report Generation Based on Multi-Modal Large Models

CSD-VAR: Content-Style Decomposition in Visual Autoregressive Models

A segmented robot grasping perception neural network for edge AI

Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need

DUALRec: A Hybrid Sequential and Language Model Framework for Context-Aware Movie Recommendation

Exploiting Primacy Effect To Improve Large Language Models

Generalist Forecasting with Frozen Video Models via Latent Diffusion

Convergent transformations of visual representation in brains and models

Preprint: Did I Just Browse A Website Written by LLMs?

The Levers of Political Persuasion with Conversational AI

Political Leaning and Politicalness Classification of Texts

Self-supervised learning on gene expression data

Using LLMs to identify features of personal and professional skills in an open-response situational judgment test

Single- to multi-fidelity history-dependent learning with uncertainty quantification and disentanglement: application to data-driven constitutive modeling

Created by

Haebom

作者

Jiaxiang Yi, Bernardo P. Ferreira, Miguel A. Bessa

概要

この論文では、データ駆動型学習を拡張し、歴史に依存する多重忠実度データを考慮し、認識的不確実性を定量化し、データノイズ（確率的不確実性）から分離する方法について説明します。階層構造を持つこの方法は、単純な単一忠実度決定論的ニューラルネットワーク学習から提案された複数忠実度分散推定ベイズ循環ニューラルネットワーク学習まで、さまざまな学習シナリオに適用できます。さまざまな忠実度のデータ(ノイズの有無を含む)を使用する複数のデータ駆動型構成モデリングシナリオに適用することにより,方法の多様性と一般性を実証した。この方法は、応答を正確に予測し、モデル誤差を定量化し、ノイズ分布（存在する場合）を特定します。これは、不確実性の下での設計と分析を含む最も困難なケースを含む、さまざまな科学および工学分野の実際のアプリケーションの機会を開きます。

Takeaways、Limitations

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Takeaways:

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歴史依存多重忠実度データを用いたデータ駆動型学習の一般化可能性の提示

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認識的不確実性と確率的不確実性の分離と定量化

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さまざまな学習シナリオ（単一/多重忠実度、決定論的/ベイジアン）に適用可能な柔軟な方法論の提示

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モデル誤差の定量化と雑音分布の把握による正確な応答予測

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不確実性の下で設計と分析を含む様々な科学/工学分野の応用可能性を提示

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Limitations：

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本論文で提示した方法論の実際の応用事例の具体的な分析の欠如

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さまざまなデータセットの一般化パフォーマンスの追加検証が必要

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計算コストと複雑さの評価不足

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特定の種類のデータまたは問題に対する偏りの可能性の存在

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