haebom
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。
Language Models are Injective and Hence Invertible
Learning to Detect Unknown Jailbreak Attacks in Large Vision-Language Models
Latent Diffusion Model without Variational Autoencoder
Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning
CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions
Architecture Is All You Need: Diversity-Enabled Sweet Spots for Robust Humanoid Locomotion
LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching
Knowledge-based Visual Question Answer with Multimodal Processing, Retrieval and Filtering
STANCE: Motion Coherent Video Generation Via Sparse-to-Dense Anchored Encoding
MedTrust-RAG: Evidence Verification and Trust Alignment for Biomedical Question Answering
Beyond One World: Benchmarking Super Heros in Role-Playing Across Multiversal Contexts
Static Sandboxes Are Inadequate: Modeling Societal Complexity Requires Open-Ended Co-Evolution in LLM-Based Multi-Agent Simulations
Deflanderization for Game Dialogue: Balancing Character Authenticity with Task Execution in LLM-based NPCs
ConsintBench: Evaluating Language Models on Real-World Consumer Intent Understanding
Max It or Miss It: Benchmarking LLM On Solving Extremal Problems
Phenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging
When Does Supervised Training Pay Off? The Hidden Economics of Object Detection in the Era of Vision-Language Models
The Curious Case of Factual (Mis)Alignment between LLMs' Short- and Long-Form Answers
A Vision for Access Control in LLM-based Agent Systems
Audit-of-Understanding: Posterior-Constrained Inference for Mathematical Reasoning in Language Models
Formally Verified Certification of Unsolvability of Temporal Planning Problems
DICE: Structured Reasoning in LLMs through SLM-Guided Chain-of-Thought Correction
MSDM: Generating Task-Specific Pathology Images with a Multimodal Conditioned Diffusion Model for Cell and Nuclei Segmentation
Synthetic Series-Symbol Data Generation for Time Series Foundation Models
SDAR: A Synergistic Diffusion-AutoRegression Paradigm for Scalable Sequence Generation
Online automatic code generation for robot swarms: LLMs and self-organizing hierarchy
A New Digital Divide? Coder Worldviews, the Slop Economy, and Democracy in the Age of AI
Audit the Whisper: Detecting Steganographic Collusion in Multi-Agent LLMs
Creative synthesis of kinematic mechanisms
Market-Driven Subset Selection for Budgeted Training
Mini-vec2vec: Scaling Universal Geometry Alignment with Linear Transformations
A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation
TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting
Learning Generalizable Shape Completion with SIM(3) Equivariance
Dolphin v1.0 Technical Report
A Measurement Study of Model Context Protocol Ecosystem
Diffusion Models are Kelly Gamblers
RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
Semantic Representation Attack against Aligned Large Language Models
Chiplet-Based RISC-V SoC with Modular AI Acceleration
Accurate and Efficient Low-Rank Model Merging in Core Space
The 1st Solution for 7th LSVOS RVOS Track: SaSaSa2VA
Graph Coloring for Multi-Task Learning
Robust LLM Training Infrastructure at ByteDance
RPG: A Repository Planning Graph for Unified and Scalable Codebase Generation
Communications to Circulations: Real-Time 3D Wind Field Prediction Using 5G GNSS Signals and Deep Learning
Why and How Auxiliary Tasks Improve JEPA Representations
Creativity Benchmark: A benchmark for marketing creativity for large language models
SpikingBrain: Spiking Brain-inspired Large Models
Robust Pan-Cancer Mitotic Figure Detection with YOLOv12
BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design
A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
FlowDet: Overcoming Perspective and Scale Challenges in Real-Time End-to-End Traffic Detection
Epistemic Trade-Off: An Analysis of the Operational Breakdown and Ontological Limits of "Certainty-Scope" in AI
ZeST: an LLM ベースの Zero-Shot Traversability Navigation for Unknown Environments
Interpretable Decision-Making for End-to-End Autonomous Driving
A Systematic Approach to Predict the Impact of Cybersecurity Vulnerabilities Using LLMs
Limitations of Normalization in Attention Mechanism
Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning
The GPT-4o Shock Emotional Attachment to AI Models and Its Impact on Regulatory Acceptance: A Cross-Cultural Analysis of the Immediate Transition from GPT-4o to GPT-5
CorrSteer: Generation-Time LLM Steering via Correlated Sparse Autoencoder Features
VimoRAG: Video-based Retrieval-augmented 3D Motion Generation for Motion Language Models
SegDAC: Improving Visual Reinforcement Learning by Extracting Dynamic Objectc-Centric Representations from Pretrained Vision Models
VGGSounder: Audio-Visual Evaluations for Foundation Models
Evolution of AI Agent Registry Solutions: Centralized, Enterprise, and Distributed Approaches
CAPO: Towards Enhancing LLM Reasoning through Generative Credit Assignment
FGBench: A Dataset and Benchmark for Molecular Property Reasoning at Functional Group-Level in Large Language Models
SketchMind: A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches
A Multi-Stage Hybrid CNN-Transformer Network for Automated Pediatric Lung Sound Classification
From Individual Learning to Market Equilibrium: Correcting Structural and Parametric Biases in RL Simulations of Economic Models
ReDi: Rectified Discrete Flow
Adaptive Policy Synchronization for Scalable Reinforcement Learning
From Sequence to Structure: Uncovering Substructure Reasoning in Transformers
Multimodal Fusion at Three Tiers: Physics-Driven Data Generation and Vision-Language Guidance for Brain Tumor Segmentation
Controlling What You Share: Assessing Language Model Adherence to Privacy Preferences
DP-Fusion: Token-Level Differentially Private Inference for Large Language Models
AI-Generated Video Detection via Perceptual Straightening
From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging
Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learning
ADA-DPM: A Neural Descriptors-based Adaptive Noise Filtering Strategy for SLAM
GeNIE: A Generalizable Navigation System for In-the-Wild Environments
From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
Every Rollout Counts: Optimal Resource Allocation for Efficient Test-Time Scaling
PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation
Code Execution as Grounded Supervision for LLM Reasoning
Denoising the Future: Top-p Distributions for Moving Through Time
HauntAttack: When Attack Follows Reasoning as a Shadow
RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics
Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing
VisuRiddles: Fine-grained Perception is a Primary Bottleneck for Multimodal Large Language Models in Abstract Visual Reasoning
CoVoMix2: Advancing Zero-Shot Dialogue Generation with Fully Non-Autoregressive Flow Matching
KG-TRACES: Enhancing Large Language Models with Knowledge Graph-constrained Trajectory Reasoning and Attribution Supervision
SATA-BENCH: Select All That Apply Benchmark for Multiple Choice Questions
REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
VERINA: Benchmarking Verifiable Code Generation
RocqStar: Leveraging Similarity-driven Retrieval and Agentic Systems for Rocq generation
The quest for the GRAph Level autoEncoder (GRALE)
Efficient Large Language Model Inference with Neural Block Linearization
DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning
Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models
Load more
Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learning
Created by
Haebom
作者
Mohammad Mahdi Maheri, Denys Herasymuk, Hamed Haddadi
P4: Personalized, Private, Peer-to-Peer Learning for IoT
概要
P4は、IoT環境でリソースが限られたデバイス用にパーソナライズされたモデルを提供するために設計された方法です。差分プライバシーを確保し、ポイズニング攻撃に対する強力な防御機能を提供します。この方法は、軽量化された完全分散アルゴリズムを使用して、クライアントの類似性を非公開で検出し、コラボレーショングループを形成します。各グループ内で、クライアントは差分プライバシー知識蒸留を利用してモデルを共同訓練し、悪意のあるクライアントの存在にも高い精度を維持します。
Takeaways、Limitations
•
Takeaways：
◦
リソース制約のあるIoTデバイスのためのパーソナライズされた学習モデルを提供します。
◦
差分プライバシー保証とポイズニング攻撃に対する高い防御力
◦
先行研究と比較して5％から30％の高精度を達成。
◦
悪意のあるクライアントが30％まで存在しても強力なパフォーマンスを維持。
◦
リソース制約のあるデバイスでも実用的に適用可能で、コラボレーショントレーニングのオーバーヘッドが非常に少ない（2つのクライアント間で約7秒）。
•
Limitations：
◦
論文に具体的なLimitationsへの言及はありません。
PDFを見る
Made with Slashpage
