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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。
Merge-of-Thought Distillation
OTESGN: Optimal Transport-Enhanced Syntactic-Semantic Graph Networks for Aspect-Based Sentiment Analysis
MESH - Understanding Videos Like Human: Measuring Hallucinations in Large Video Models
Adapting Vision-Language Models for Neutrino Event Classification in High-Energy Physics
Symmetry-Guided Multi-Agent Inverse Reinforcement Learning
AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs
Expert-Guided Explainable Few-Shot Learning for Medical Image Diagnosis
Towards Generalized Routing: Model and Agent Orchestration for Adaptive and Efficient Inference
MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining
Demo: Healthcare Agent Orchestrator (HAO) for Patient Summarization in Molecular Tumor Boards
Focusing by Contrastive Attention: Enhancing VLMs' Visual Reasoning
Beyond the Pre-Service Horizon: Infusing In-Service Behavior for Improved Financial Risk Forecasting
On Synthesis of Timed Regular Expressions
TinyDef-DETR: A DETR-based Framework for Defect Detection in Transmission Lines from UAV Imagery
LiDAR-BIND-T: Improved and Temporally Consistent Sensor Modality Translation and Fusion for Robotic Applications
From Vision to Validation: A Theory- and Data-Driven Construction of a GCC-Specific AI Adoption Index
A Comprehensive Guide to Differential Privacy: From Theory to User Expectations
The Architecture of AI Transformation: Four Strategic Patterns and an Emerging Frontier
FLM-Audio: Natural Monologues Improves Native Full-Duplex Chatbots via Dual Training
Deep Learning-Based Rock Particulate Classification Using Attention-Enhanced ConvNeXt
The Information Dynamics of Generative Diffusion
Data-Augmented Few-Shot Neural Stencil Emulation for System Identification of Computer Models
Group Expectation Policy Optimization for Heterogeneous Reinforcement Learning
Pretrained Conformers for Audio Fingerprinting and Retrieval
Towards Scalable Training for Handwritten Mathematical Expression Recognition
To Theoretically Understand Transformer-Based In-Context Learning for Optimizing CSMA
Klear-CodeTest: Scalable Test Case Generation for Code Reinforcement Learning
HiD-VAE: Interpretable Generative Recommendation via Hierarchical and Disentangled Semantic IDs
MagicGUI: A Foundational Mobile GUI Agent with Scalable Data Pipeline and Reinforcement Fine-tuning
Villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models
New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants
Can Large Language Models Understand As Well As Apply Patent Regulations to Pass a Hands-On Patent Attorney Test?
Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound
Uncertainty Estimation by Human Perception versus Neural Models
Persistent Homology of Topic Networks for the Prediction of Reader Curiosity
Task Matters: Knowledge Requirements Shape LLM Responses to Context-Memory Conflict
Crack Path Prediction with Operator Learning using Discrete Particle System data Generation
Diffusion Graph Neural Networks for Robustness in Olfaction Sensors and Datasets
MM-Prompt: Cross-Modal Prompt Tuning for Continual Visual Question Answering
An Ontology-Driven Graph RAG for Legal Norms: A Structural, Temporal, and Deterministic Approach
Combating Falsification of Speech Videos with Live Optical Signatures (Extended Version)
Early Exit and Multi Stage Knowledge Distillation in VLMs for Video Summarization
Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Review
Parasite: A Steganography-based Backdoor Attack Framework for Diffusion Models
Towards Adaptive Memory-Based Optimization for Enhanced Retrieval-Augmented Generation
Entropy-Gated Branching for Efficient Test-Time Reasoning
SWI: Speaking with Intent in Large Language Models
Byzantine-Robust Federated Learning Using Generative Adversarial Networks
VeriSafe Agent: Safeguarding Mobile GUI Agent via Logic-based Action Verification
MIND: Towards Immersive Psychological Healing with Multi-agent Inner Dialogue
V-HOP: Visuo-Haptic 6D Object Pose Tracking
EgoAgent: A Joint Predictive Agent Model in Egocentric Worlds
Knowledge-Guided Biomarker Identification for Label-Free Single-Cell RNA-Seq Data: A Reinforcement Learning Perspective
MERaLiON-SpeechEncoder: Towards a Speech Foundation Model for Singapore and Beyond
RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution
IDEATOR: Jailbreaking and Benchmarking Large Vision-Language Models Using Themselves
DeepVoting: Learning and Fine-Tuning Voting Rules with Canonical Embeddings
Rethinking Disentanglement under Dependent Factors of Variation
Discovering physical laws with parallel symbolic enumeration
Semantic Augmentation in Images using Language
Algorithmic Collusion by Large Language Models
A minimal coalition logic
Deep Reinforcement Learning for Inventory Networks: Toward Reliable Policy Optimization
Inconsistency Handling in Prioritized Databases with Universal Constraints: Complexity Analysis and Links with Active Integrity Constraints
Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference
CogGuide: Human-Like Guidance for Zero-Shot Omni-Modal Reasoning
TreeGPT: Pure TreeFFN Encoder-Decoder Architecture for Structured Reasoning Without Attention Mechanisms
Robix: A Unified Model for Robot Interaction, Reasoning and Planning
KROMA: Ontology Matching with Knowledge Retrieval and Large Language Models
Scaling LLM Planning: NL2FLOW for Parametric Problem Generation and Rigorous Evaluation
Optimizing Length Compression in Large Reasoning Models
LLMs for sensory-motor control: Combining in-context and iterative learning
Effort-aware Fairness: Incorporating a Philosophy-informed, Human-centered Notion of Effort into Algorithmic Fairness Metrics
Simulating Human-like Daily Activities with Desire-driven Autonomy
Enhancing Few-Shot Transfer Learning with Optimized Multi-Task Prompt Tuning through Modular Prompt Composition
ButterflyQuant: Ultra-low-bit LLM Quantization through Learnable Orthogonal Butterfly Transforms
CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
Feasibility-Guided Fair Adaptive Offline Reinforcement Learning for Medicaid Care Management
Retrieval-Augmented Generation for Reliable Interpretation of Radio Regulations
Explaining Concept Drift through the Evolution of Group Counterfactuals
LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering
Mechanistic Learning with Guided Diffusion Models to Predict Spatio-Temporal Brain Tumor Growth
Graph Alignment via Dual-Pass Spectral Encoding and Latent Space Communication
ObjectReact: Learning Object-Relative Control for Visual Navigation
Fluent but Unfeeling: The Emotional Blind Spots of Language Models
Invisible Attributes, Visible Biases: Exploring Demographic Shortcuts in MRI-based Alzheimer's Disease Classification
An improved educational competition optimizer with multi-covariance learning operators for global optimization problems
Improving Video Diffusion Transformer Training by Multi-Feature Fusion and Alignment from Self-Supervised Vision Encoders
A modified RIME algorithm with covariance learning and diversity enhancement for numerical optimization
Towards Explainable Job Title Matching: Leveraging Semantic Textual Relatedness and Knowledge Graphs
Explainable AI for Accelerated Microstructure Imaging: A SHAP-Guided Protocol on the Connectome 2.0 scanner
Incorporating AI Incident Reporting into Telecommunications Law and Policy: Insights from India
OpenFake: An Open Dataset and Platform Toward Large-Scale Deepfake Detection
Prompt Pirates Need a Map: Stealing Seeds helps Stealing Prompts
Resource-Efficient Glioma Segmentation on Sub-Saharan MRI
ENSI: Efficient Non-Interactive Secure Inference for Large Language Models
We're Still Doing It (All) Wrong: Recommender Systems, Fifteen Years Later
LLMs Don't Know Their Own Decision Boundaries: The Unreliability of Self-Generated Counterfactual Explanations
MetaLLMix : An XAI Aided LLM-Meta-learning Based Approach for Hyper-parameters Optimization
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Inconsistency Handling in Prioritized Databases with Universal Constraints: Complexity Analysis and Links with Active Integrity Constraints
Created by
Haebom
作者
Meghyn Bienvenu, Camille Bourgaux
概要
本論文は,普遍的な制約をもつミスマッチデータベースの回復とクエリの問題を再検討した。一貫性を回復するために、事実の削除と追加の両方を使用する対称差回復を採用し、優先順位関係を介して優先回復操作を指定します。既存の最適復旧概念をより豊富な環境に拡張し,復旧確認と不一致許容照会応答のデータ複雑性を研究する。最後に、優先順位データベースの最適回復とアクティブ整合性制約フレームワークで導入された回復概念との関係を明確にし、特に本論文のPareto-最適回復がアクティブ整合性制約に該当することを示す。この研究は、アクティブな完全性制約の動作に関する有用な洞察を提供します。
Takeaways、Limitations
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Takeaways：
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普遍的な制約の下で対称差復旧を用いる不整合データベース復旧と照会に対する新しいアプローチの提示
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既存の最適回復概念をより一般的な設定に拡張。
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リカバリ検証と不一致許容クエリ応答のデータ複雑性解析
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優先順位データベースの最適回復とアクティブ整合性制約との関係解明
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アクティブな整合性制約の動作に関する新しい洞察を提供
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Limitations：
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実データベースシステムの実験的評価の欠如
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特定の種類の優先順位関係または制約の制限。
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より複雑なクエリ言語または制約の一般化の必要性。
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