Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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Inductive Moment Matching

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms

FaceID-6M: A Large-Scale, Open-Source FaceID Customization Dataset

Interactive Medical Image Analysis with Concept-based Similarity Reasoning

Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

LightMotion: A Light and Tuning-free Method for Simulating Camera Motion in Video Generation

A Transformer Model for Predicting Chemical Reaction Products from Generic Templates

CBW: Towards Dataset Ownership Verification for Speaker Verification via Clustering-based Backdoor Watermarking

The Lazy Student's Dream: ChatGPT Passing an Engineering Course on Its Own

VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control

Multi-Task Reinforcement Learning Enables Parameter Scaling

Balcony: A Lightweight Approach to Dynamic Inference of Generative Language Models

Prediction of Frozen Region Growth in Kidney Cryoablation Intervention Using a 3D Flow-Matching Model

Call for Rigor in Reporting Quality of Instruction Tuning Data

KunlunBaize: LLM with Multi-Scale Convolution and Multi-Token Prediction Under TransformerX Framework

(How) Do Language Models Track State?

IterPref: Focal Preference Learning for Code Generation via Iterative Debugging

PaCA: Partial Connection Adaptation for Efficient Fine-Tuning

Forgotten Polygons: Multimodal Large Language Models are Shape-Blind

Q-PETR: Quant-aware Position Embedding Transformation for Multi-View 3D Object Detection

FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling

Helix-mRNA: A Hybrid Foundation Model For Full Sequence mRNA Therapeutics

IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation

Reasoning-Augmented Conversation for Multi-Turn Jailbreak Attacks on Large Language Models

Equivariant Masked Position Prediction for Efficient Molecular Representation

IRepair: An Intent-Aware Approach to Repair Data-Driven Errors in Large Language Models

Automated Consistency Analysis of LLMs

ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates

Rationalization Models for Text-to-SQL

Reflection-Window Decoding: Text Generation with Selective Refinement

Agentic Bug Reproduction for Effective Automated Program Repair at Google

Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning

MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods

KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks

TexAVi: Generating Stereoscopic VR Video Clips from Text Descriptions

Multi-P$^2$A: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models

Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training

SweetTok: Semantic-Aware Spatial-Temporal Tokenizer for Compact Video Discretization

DMin: Scalable Training Data Influence Estimation for Diffusion Models

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents

LayoutVLM: Differentiable Optimization of 3D Layout via Vision-Language Models

RL-MILP Solver: A Reinforcement Learning Approach for Solving Mixed-Integer Linear Programs with Graph Neural Networks

Proto Successor Measure: Representing the Behavior Space of an RL Agent

KinMo: Kinematic-aware Human Motion Understanding and Generation

Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks

OminiControl: Minimal and Universal Control for Diffusion Transformer

MTA: Multimodal Task Alignment for BEV Perception and Captioning

PyGen: A Collaborative Human-AI Approach to Python Package Creation

Fair Summarization: Bridging Quality and Diversity in Extractive Summaries

AtlasSeg: Atlas Prior Guided Dual-U-Net for Cortical Segmentation in Fetal Brain MRI

V-LoRA: An Efficient and Flexible System Boosts Vision Applications with LoRA LMM

Fourier Head: Helping Large Language Models Learn Complex Probability Distributions

Conditional diffusions for neural posterior estimation

LLM-HDR: Bridging LLM-based Perception and Self-Supervision for Unpaired LDR-to-HDR Image Reconstruction

Chemistry-Inspired Diffusion with Non-Differentiable Guidance

Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion

6DGS: Enhanced Direction-Aware Gaussian Splatting for Volumetric Rendering

CAX: Cellular Automata Accelerated in JAX

Emotion-Aware Embedding Fusion in LLMs (Flan-T5, LLAMA 2, DeepSeek-R1, and ChatGPT 4) for Intelligent Response Generation

What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach

Meta-RTL: Reinforcement-Based Meta-Transfer Learning for Low-Resource Commonsense Reasoning

LEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks

Training with Differential Privacy: A Gradient-Preserving Noise Reduction Approach with Provable Security

ASMA: An Adaptive Safety Margin Algorithm for Vision-Language Drone Navigation via Scene-Aware Control Barrier Functions

Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Inference-Time Selective Debiasing to Enhance Fairness in Text Classification Models

Detect, Investigate, Judge and Determine: A Knowledge-guided Framework for Few-shot Fake News Detection

How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective

Value Improved Actor Critic Algorithms

Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search

Curriculum Direct Preference Optimization for Diffusion and Consistency Models

Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering

RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion

Adversarial Guided Diffusion Models for Adversarial Purification

M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling

The VampPrior Mixture Model

Regularization by Texts for Latent Diffusion Inverse Solvers

Deep Tensor Network

Identifying the Truth of Global Model: A Generic Solution to Defend Against Byzantine and Backdoor Attacks in Federated Learning (full version)

Generalizable Imitation Learning Through Pre-Trained Representations

Hypergraph Structure Inference From Data Under Smoothness Prior

HowkGPT: Investigating the Detection of ChatGPT-generated University Student Homework through Context-Aware Perplexity Analysis

SketchOGD: Memory-Efficient Continual Learning

ChatGPT-4 in the Turing Test: A Critical Analysis

Toward an Evaluation Science for Generative AI Systems

WritingBench: A Comprehensive Benchmark for Generative Writing

ToolFuzz -- Automated Agent Tool Testing

Building Interval Type-2 Fuzzy Membership Function: A Deck of Cards based Co-constructive Approach

Optimus-2: Multimodal Minecraft Agent with Goal-Observation-Action Conditioned Policy

Learning to Plan with Personalized Preferences

Exponential Speedups by Rerooting Levin Tree Search

A Unified Framework for Motion Reasoning and Generation in Human Interaction

Agent-Oriented Planning in Multi-Agent Systems

Dynamic Analysis and Adaptive Discriminator for Fake News Detection

A Practical Review of Mechanistic Interpretability for Transformer-Based Language Models

AI Data Readiness Inspector (AIDRIN) for Quantitative Assessment of Data Readiness for AI

Nondeterministic Causal Models

X-SHIELD: Regularization for eXplainable Artificial Intelligence

Categorical semantics of compositional reinforcement learning

Building Interval Type-2 Fuzzy Membership Function: A Deck of Cards based Co-constructive Approach

Created by

Haebom

저자

Bapi Dutta, Diego Garcia-Zamora, Jose Rui Figueira, Luis Martinez

개요

본 논문은 의사결정 과정에서의 불확실성과 모호성을 다루는 데 널리 사용되는 퍼지 집합의 한계를 극복하기 위해, 의사결정자의 주관적인 판단에 대한 불확실성을 고려하는 구간 유형 2 퍼지 집합(IT2FS) 모델링 방법을 제시한다. 기존 IT2FS 구성 방법의 의사결정자 참여 부족 문제를 해결하고자, 의사결정자의 적극적인 참여를 유도하는 사회기술적 공동 구성 접근 방식을 제안한다. 이는 수정된 카드덱(DoC) 방법을 이용하여 비율척도 상에서 유형 1 퍼지 집합(T1FS) 멤버십 함수를 구성하고, 이를 확장하여 주관적 판단의 모호성을 포함하는 IT2FS 모델을 만드는 두 단계로 구성된다. 두 번째 단계에서는 구성된 IT2FS 모델을 다기준 의사결정(MCDM)에 적용하기 위한 수학적 표현, 집계 규칙 및 허용 가능한 순서 원리를 정의한다. 제안된 프레임워크는 의사결정자의 개인화된 의미를 정확하게 반영하여 퍼지 의사결정의 신뢰성과 효율성을 높인다.

시사점, 한계점

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시사점:

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의사결정자의 적극적인 참여를 유도하는 사회기술적 공동 구성 접근 방식을 통해 더욱 신뢰할 수 있고 효과적인 IT2FS 모델을 구축할 수 있다.

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수정된 카드덱(DoC) 방법을 이용하여 의사결정자의 주관적인 판단을 보다 정확하게 반영할 수 있다.

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구축된 IT2FS 모델을 다기준 의사결정(MCDM) 문제에 적용하기 위한 수학적 표현, 집계 규칙 및 순서 원리를 제시하여 실제 문제 해결에 활용 가능성을 높였다.

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의사결정자의 개인화된 의미를 정확하게 반영하여 퍼지 의사결정의 신뢰성과 효율성을 향상시킨다.

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한계점:

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제안된 방법의 효율성 및 일반화 가능성에 대한 추가적인 실증 연구가 필요하다.

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다양한 유형의 MCDM 문제에 대한 적용성 및 확장성 검증이 필요하다.

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수정된 카드덱(DoC) 방법의 매개변수 설정 및 최적화에 대한 추가적인 연구가 필요할 수 있다.

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의사결정자의 참여를 유도하는 과정에서 발생할 수 있는 시간 및 비용적인 제약에 대한 고려가 필요하다.

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