haebom
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.
AI/ML in 3GPP 5G Advanced -- Services and Architecture
CookAnything: A Framework for Flexible and Consistent Multi-Step Recipe Image Generation
Dynamic Correction of Erroneous State Estimates via Diffusion Bayesian Exploration
Concept-Guided Backdoor Attack on Vision Language Models
On the Holographic Geometry of Deterministic Computation
Decoding inner speech with an end-to-end brain-to-text neural interface
Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation
MindEval: Benchmarking Language Models on Multi-turn Mental Health Support
LAET: A Layer-wise Adaptive Ensemble Tuning Framework for Pretrained Language Models
FAST-CAD: A Fairness-Aware Framework for Non-Contact Stroke Diagnosis
Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale
SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control
MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling
Data-Augmented Deep Learning for Downhole Depth Sensing and Field Validation
Chinese Discharge Drug Recommendation in Metabolic Diseases with Large Language Models
Analysing Moral Bias in Finetuned LLMs through Mechanistic Interpretability
Orders in Chaos: Enhancing Large-Scale MoE LLM Serving with Data Movement Forecasting
Reinforce-Ada: An Adaptive Sampling Framework under Non-linear RL Objectives
TempoControl: Temporal Attention Guidance for Text-to-Video Models
AortaDiff: A Unified Multitask Diffusion Framework For Contrast-Free AAA Imaging
SoREX: Towards Self-Explainable Social Recommendation with Relevant Ego-Path Extraction
The AI Productivity Index (APEX)
Uncovering Grounding IDs: How External Cues Shape Multimodal Binding
Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization
V-CECE: Visual Counterfactual Explanations via Conceptual Edits
Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios
HARP: Hallucination Detection via Reasoning Subspace Projection
Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone
IPA: An Information-Reconstructive Input Projection Framework for Efficient Foundation Model Adaptation
Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal
Retro-Expert: Collaborative Reasoning for Interpretable Retrosynthesis
A Survey on Diffusion Language Models
CodeNER: Code Prompting for Named Entity Recognition
ReSem3D: Refinable 3D Spatial Constraints via Fine-Grained Semantic Grounding for Generalizable Robotic Manipulation
VERIRAG: A Post-Retrieval Auditing of Scientific Study Summaries
SustainDiffusion: Optimising the Social and Environmental Sustainability of Stable Diffusion Models
LittleBit: Ultra Low-Bit Quantization via Latent Factorization
Real-Time Execution of Action Chunking Flow Policies
AURA: A Diagnostic Framework for Tracking User Satisfaction of Interactive Planning Agents
Enhancing SPARQL Query Rewriting for Complex Ontology Alignments
Exploring Ordinal Bias in Action Recognition for Instructional Videos
Robust Weight Imprinting: Insights from Neural Collapse and Proxy-Based Aggregation
Experiments with Large Language Models on Retrieval-Augmented Generation for Closed-Source Simulation Software
SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models
Large Language Models: An Applied Econometric Framework
Edge-Only Universal Adversarial Attacks in Distributed Learning
Image-Guided Semantic Pseudo-LiDAR Point Generation for 3D Object Detection
Detecting the Future: All-at-Once Event Sequence Forecasting with Horizon Matching
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling
SOAP: Enhancing Spatio-Temporal Relation and Motion Information Capturing for Few-Shot Action Recognition
A Scene-aware Models Adaptation Scheme for Cross-scene Online Inference on Mobile Devices
Towards Data-efficient Customer Intent Recognition with Prompt-based Learning Paradigm
GTM: Simulating the World of Tools for AI Agents
Self-Transparency Failures in Expert-Persona LLMs: How Instruction-Following Overrides Honesty
Learning the Value of Value Learning
OpenMMReasoner: Pushing the Frontiers for Multimodal Reasoning with an Open and General Recipe
ToolMind Technical Report: A Large-Scale, Reasoning-Enhanced Tool-Use Dataset
Debate over Mixed-knowledge: A Robust Multi-Agent Reasoning Framework for Incomplete Knowledge Graph Question Answering
Spilling the Beans: Teaching LLMs to Self-Report Their Hidden Objectives
Counterfactual Reasoning for Steerable Pluralistic Value Alignment of Large Language Models
Generalized Parallel Scaling with Interdependent Generations
SOCK: A Benchmark for Measuring Self-Replication in Large Language Models
KNARsack: Teaching Neural Algorithmic Reasoners to Solve Pseudo-Polynomial Problems
IS-Bench: Evaluating Interactive Safety of VLM-Driven Embodied Agents in Daily Household Tasks
FedIFL: A federated cross-domain diagnostic framework for motor-driven systems with inconsistent fault modes
Enhancing Large Language Models through Neuro-Symbolic Integration and Ontological Reasoning
Rolling in the deep of cognitive and AI biases
Enhancing Retrieval-Augmented Generation with Entity Linking for Educational Platforms
Training-Time Action Conditioning for Efficient Real-Time Chunking
Whatever Remains Must Be True: Filtering Drives Reasoning in LLMs, Shaping Diversity
AQUA-Net: Adaptive Frequency Fusion and Illumination Aware Network for Underwater Image Enhancement
M4-RAG: A Massive-Scale Multilingual Multi-Cultural Multimodal RAG
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution
Trusted AI Agents in the Cloud
Impugan: Learning Conditional Generative Models for Robust Data Imputation
Zoom in, Click out: Unlocking and Evaluating the Potential of Zooming for GUI Grounding
Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception
World Models That Know When They Don't Know: Controllable Video Generation with Calibrated Uncertainty
Natural Language Summarization Enables Multi-Repository Bug Localization by LLMs in Microservice Architectures
Neural Coherence : Find higher performance to out-of-distribution tasks from few samples
Sparse Attention Post-Training for Mechanistic Interpretability
Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework
NEAT: Neighborhood-Guided, Efficient, Autoregressive Set Transformer for 3D Molecular Generation
Phase-OTDR Event Detection Using Image-Based Data Transformation and Deep Learning
Approximation of Box Decomposition Algorithm for Fast Hypervolume-Based Multi-Objective Optimization
Probing the effectiveness of World Models for Spatial Reasoning through Test-time Scaling
3D Path Planning for Robot-assisted Vertebroplasty from Arbitrary Bi-plane X-ray via Differentiable Rendering
Mechanistic Interpretability of Antibody Language Models Using SAEs
Active Video Perception: Iterative Evidence Seeking for Agentic Long Video Understanding
Efficient Text Classification with Conformal In-Context Learning
Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias
Bayesian Active Inference for Intelligent UAV Anti-Jamming and Adaptive Trajectory Planning
Faithfulness metric fusion: Improving the evaluation of LLM trustworthiness across domains
Retrieving Semantically Similar Decisions under Noisy Institutional Labels: Robust Comparison of Embedding Methods
InverseCrafter: Efficient Video ReCapture as a Latent Domain Inverse Problem
Feasibility of AI-Assisted Programming for End-User Development
Grounded Multilingual Medical Reasoning for Question Answering with Large Language Models
Modular Jets for Supervised Pipelines: Diagnosing Mirage vs Identifiability
A Comprehensive Framework for Automated Quality Control in the Automotive Industry
Load more
Towards Stable and Structured Time Series Generation with Perturbation-Aware Flow Matching
Created by
Haebom
Category
Empty
저자
Jintao Zhang, Mingyue Cheng, Zirui Liu, Xianquan Wang, Yitong Zhou, Qi Liu
개요
본 논문은 구조적으로 일관된 시계열 생성을 위해 고안된 Perturbation-Aware Flow Matching (PAFM) 프레임워크를 소개한다. PAFM은 국소적 섭동으로 인한 시계열의 구조적 변화를 효과적으로 모델링하기 위해 섭동 유도 훈련과 이중 경로 속도장을 활용한다. 또한, 혼합 전문가 디코더를 통해 다양한 궤적 역학에 동적으로 대응하며, 무조건적 및 조건부 생성 작업에서 기존 모델들을 능가하는 성능을 보인다.
시사점, 한계점
•
섭동에 민감하고 구조적으로 일관된 시계열 생성을 위한 새로운 프레임워크 제시
•
섭동 유도 훈련 및 이중 경로 속도장 활용을 통해 섭동된 궤적의 변화를 효과적으로 모델링
•
혼합 전문가 디코더를 통해 모델의 표현력 향상
•
강력한 기준선을 능가하는 우수한 성능 입증
•
코드 공개를 통해 재현 가능성 확보
•
논문에서 구체적인 한계점 언급은 없음.
PDF 보기
Made with Slashpage
