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Daily Arxiv
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。
HPC Digital Twins for Evaluating Scheduling Policies, Incentive Structures and their Impact on Power and Cooling
NLKI: A lightweight Natural Language Knowledge Integration Framework for Improving Small VLMs in Commons VQA Tasks
Interact-Custom: Customized Human Object Interaction Image Generation
A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation
MIDAS: Multimodal Interactive Digital-humAn Synthesis via Real-time Autoregressive Video Generation
From Tabula Rasa to Emergent Abilities: Discovering Robot Skills via Real-World Unsupervised Quality-Diversity
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks
STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems
LLMs Can't Handle Peer Pressure: Crumbling under Multi-Agent Social Interactions
Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning
Modality-Specific Speech Enhancement and Noise-Adaptive Fusion for Acoustic and Body-Conduction Microphone Framework
Humans Perceive Wrong Narratives from AI Reasoning Texts
SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning
Pareto Actor-Critic for Communication and Computation Co-Optimization in Non-Cooperative Federated Learning Services
Learning to Drive Ethically: Embedding Moral Reasoning into Autonomous Driving
Generative AI Against Poaching: Latent Composite Flow Matching for Wildlife Conservation
Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)
Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics
Steering Towards Fairness: Mitigating Political Bias in LLMs
Dynamic Context Compression for Efficient RAG
Irredundant $k$-Fold Cross-Validation
Prompt Engineering and the Effectiveness of Large Language Models in Enhancing Human Productivity
A Highly Clean Recipe Dataset with Ingredient States Annotation for State Probing Task
Entropy-Memorization Law: Evaluating Memorization Difficulty of Data in LLMs
The Joys of Categorical Conformal Prediction
Adversarial Manipulation of Reasoning Models using Internal Representations
Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models
A Hybrid Artificial Intelligence Method for Estimating Flicker in Power Systems (Changes are marked)
GLProtein: Global-and-Local Structure Aware Protein Representation Learning
Program Semantic Inequivalence Game with Large Language Models
DSO: Aligning 3D Generators with Simulation Feedback for Physical Soundness
Improving Quantization with Post-Training Model Expansion
Safe and Efficient Social Navigation through Explainable Safety Regions Based on Topological Features
A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing
Federated nnU-Net for Privacy-Preserving Medical Image Segmentation
ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation
Enhancing Automated Loop Invariant Generation for Complex Programs with Large Language Models
RevPRAG: Revealing Poisoning Attacks in Retrieval-Augmented Generation through LLM Activation Analysis
Categorical Data Clustering via Value Order Estimated Distance Metric Learning
Application of AI to formal methods - an analysis of current trends
Reconsidering the Performance of GAE in Link Prediction
See then Tell: Enhancing Key Information Extraction with Vision Grounding
Enhancing Natural Language Inference Performance with Knowledge Graph for COVID-19 Automated Fact-Checking in Indonesian Language
Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics
FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference
SoAy: A Solution-based LLM API-using Methodology for Academic Information Seeking
Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off
Network Formation and Dynamics Among Multi-LLMs
NetGPT: Generative Pretrained Transformer for Network Traffic
OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset
Explainability of Text Processing and Retrieval Methods: A Survey
The Ramon Llull's Thinking Machine for Automated Ideation
RLMR: Reinforcement Learning with Mixed Rewards for Creative Writing
LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence
MSARL: Decoupling Reasoning and Tool Use with Multi-Small-Agent Reinforcement Learning
Automated Algorithmic Discovery for Gravitational-Wave Detection Guided by LLM-Informed Evolutionary Monte Carlo Tree Search
Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess
Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground
Possible Principles for Aligned Structure Learning Agents
OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale
Prompt-to-Product: Generative Assembly via Bimanual Manipulation
OnGoal: Tracking and Visualizing Conversational Goals in Multi-Turn Dialogue with Large Language Models
Mixture of Contexts for Long Video Generation
FakeParts: a New Family of AI-Generated DeepFakes
Enabling Equitable Access to Trustworthy Financial Reasoning
Veritas: Generalizable Deepfake Detection via Pattern-Aware Reasoning
Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop
Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance
ChainReaction! Structured Approach with Causal Chains as Intermediate Representations for Improved and Explainable Causal Video Question Answering
Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Trees
ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts
WoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations
ProactiveEval: A Unified Evaluation Framework for Proactive Dialogue Agents
Research Challenges in Relational Database Management Systems for LLM Queries
Quantum Verifiable Rewards for Post-Training Qiskit Code Assistant
AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning
JADES: A Universal Framework for Jailbreak Assessment via Decompositional Scoring
Learning Primitive Embodied World Models: Towards Scalable Robotic Learning
Multi-Agent Penetration Testing AI for the Web
Uncertainty Aware-Predictive Control Barrier Functions: Safer Human Robot Interaction through Probabilistic Motion Forecasting
Exploring Machine Learning and Language Models for Multimodal Depression Detection
Speech Emotion Recognition via Entropy-Aware Score Selection
Surfel-based 3D Registration with Equivariant SE(3) Features
Evaluating Compositional Generalisation in VLMs and Diffusion Models
Safer Skin Lesion Classification with Global Class Activation Probability Map Evaluation and SafeML
Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI
Signs of Struggle: Spotting Cognitive Distortions across Language and Register
Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection
Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding
SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer
Occlusion Robustness of CLIP for Military Vehicle Classification
SeqVLM: Proposal-Guided Multi-View Sequences Reasoning via VLM for Zero-Shot 3D Visual Grounding
Provable Benefits of In-Tool Learning for Large Language Models
${C}^{3}$-GS: Learning Context-aware, Cross-dimension, Cross-scale Feature for Generalizable Gaussian Splatting
Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol
EEGDM: Learning EEG Representation with Latent Diffusion Model
Generative Annotation for ASR Named Entity Correction
MobileCLIP2: Improving Multi-Modal Reinforced Training
Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning
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Pareto Actor-Critic for Communication and Computation Co-Optimization in Non-Cooperative Federated Learning Services
Created by
Haebom
作者
Renxuan Tan, Rongpeng Li, Xiaoxue Yu, Xianfu Chen, Xing Xu, Zhifeng Zhao
概要
本論文は、多数のサービスプロバイダー（SP）エコシステムにおける連合学習（FL）の非協調的なダイナミクスを解決するためのゲーム理論的マルチエージェント強化学習（MARL）フレームワークであるPAC-MCoFLを提示します。 PAC-MCoFLはサービスプロバイダをエージェントと見なし、クライアント割り当て、適応量子化、リソース割り当てを共同で最適化します。 Pareto Actor-Critic（PAC）原則と予測回帰を統合して、パレート最適平衡を達成し、異種リスクプロファイルをモデル化し、三項カテシアン分解（TCAD）メカニズムを介して高次元行動空間を効率的に管理します。また、計算の複雑さを大幅に削減するパラメータ化された推測ジェネレータを特徴とする拡張可能なバリエーションであるPAC-MCoFL-pを開発し、誤差を境界に制限します。理論的収束を保証する幅広いシミュレーションにより、既存の最新のMARLソリューションと比較して、総報酬と超体積指標（HVI）をそれぞれ約5.8％と4.2％向上させる卓越性を検証します。
Takeaways、Limitations
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Takeaways：
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多数のサービスプロバイダー環境における連合学習の効率性を向上させる新しいゲーム理論的MARLフレームワークの提示
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PAC原則と予測回帰を利用したパレート最適平衡達成と異種リスクプロファイルのモデリング
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TCADメカニズムによる高次元行動空間の効率的な管理
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スケーラブルな変形PAC-MCoFL-pによる計算の複雑さの低減と誤差境界の制限
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総報酬とHVI強化による既存の方法に対する優秀性の検証
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さまざまなデータの不均一性と拡張展開で個々のSPとシステムパフォーマンスの効果的なバランスを実現
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Limitations：
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実際の多数のサービスプロバイダ環境での実験的検証の欠如(シミュレーション結果に依存)
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PAC-MCoFL-pのパラメータ化された推測発生器の最適パラメータ設定に関するさらなる研究が必要
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さまざまなネットワークトポロジと通信遅延のロバスト性検証が必要
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