Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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Reflection Removal through Efficient Adaptation of Diffusion Transformers

Evolutionary Architecture Search through Grammar-Based Sequence Alignment

Strategic Self-Improvement for Competitive Agents in AI Labour Markets

Balanced Few-Shot Episodic Learning for Accurate Retinal Disease Diagnosis

GeoPE:A Unified Geometric Positional Embedding for Structured Tensors

Realizable Abstractions: Near-Optimal Hierarchical Reinforcement Learning

LLMs Know More Than Words: A Genre Study with Syntax, Metaphor & Phonetics

CARL: Critical Action Focused Reinforcement Learning for Multi-Step Agent

Declarative Synthesis and Multi-Objective Optimization of Stripboard Circuit Layouts Using Answer Set Programming

ReflexFlow: Rethinking Learning Objective for Exposure Bias Alleviation in Flow Matching

Developing a General Personal Tutor for Education

SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs

Language Models as Semantic Teachers: Post-Training Alignment for Medical Audio Understanding

Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates

From Symptoms to Systems: An Expert-Guided Approach to Understanding Risks of Generative AI for Eating Disorders

SoK: a Comprehensive Causality Analysis Framework for Large Language Model Security

Setting up for failure: automatic discovery of the neural mechanisms of cognitive errors

287,872 Supermassive Black Holes Masses: Deep Learning Approaching Reverberation Mapping Accuracy

YingMusic-SVC: Real-World Robust Zero-Shot Singing Voice Conversion with Flow-GRPO and Singing-Specific Inductive Biases

YingMusic-Singer: Zero-shot Singing Voice Synthesis and Editing with Annotation-free Melody Guidance

Using Machine Learning to Take Stay-or-Go Decisions in Data-driven Drone Missions

Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges

UnwrapDiff: Conditional Diffusion for Robust InSAR Phase Unwrapping

SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs

Neural Policy Composition from Free Energy Minimization

OsmT: Bridging OpenStreetMap Queries and Natural Language with Open-source Tag-aware Language Models

E3AD: An Emotion-Aware Vision-Language-Action Model for Human-Centric End-to-End Autonomous Driving

Measuring the Unspoken: A Disentanglement Model and Benchmark for Psychological Analysis in the Wild

Towards an AI Fluid Scientist: LLM-Powered Scientific Discovery in Experimental Fluid Mechanics

Large Speech Model Enabled Semantic Communication

TimesNet-Gen: Deep Learning-based Site Specific Strong Motion Generation

Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap

Topology Matters: Measuring Memory Leakage in Multi-Agent LLMs

Semi Centralized Training Decentralized Execution Architecture for Multi Agent Deep Reinforcement Learning in Traffic Signal Control

SEASON: Mitigating Temporal Hallucination in Video Large Language Models via Self-Diagnostic Contrastive Decoding

When GenAI Meets Fake News: Understanding Image Cascade Dynamics on Reddit

When Robots Should Say "I Don't Know": Benchmarking Abstention in Embodied Question Answering

A Light-Weight Large Language Model File Format for Highly-Secure Model Distribution

Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function

RRPO: Robust Reward Policy Optimization for LLM-based Emotional TTS

Multi-Loss Learning for Speech Emotion Recognition with Energy-Adaptive Mixup and Frame-Level Attention

AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees

Detection of Intoxicated Individuals from Facial Video Sequences via a Recurrent Fusion Model

PhyVLLM: Physics-Guided Video Language Model with Motion-Appearance Disentanglement

Prototype-Based Semantic Consistency Alignment for Domain Adaptive Retrieval

UW-BioNLP at ChemoTimelines 2025: Thinking, Fine-Tuning, and Dictionary-Enhanced LLM Systems for Chemotherapy Timeline Extraction

GraphBench: Next-generation graph learning benchmarking

GuidNoise: Single-Pair Guided Diffusion for Generalized Noise Synthesis

Open-Ended Goal Inference through Actions and Language for Human-Robot Collaboration

NORi: An ML-Augmented Ocean Boundary Layer Parameterization

Automating Complex Document Workflows via Stepwise and Rollback-Enabled Operation Orchestration

Explainable Parkinsons Disease Gait Recognition Using Multimodal RGB-D Fusion and Large Language Models

Dual-Stream Spectral Decoupling Distillation for Remote Sensing Object Detection

Towards 6G Native-AI Edge Networks: A Semantic-Aware and Agentic Intelligence Paradigm

Adversarial Limits of Quantum Certification: When Eve Defeats Detection

FMA-Net++: Motion- and Exposure-Aware Real-World Joint Video Super-Resolution and Deblurring

MASE: Interpretable NLP Models via Model-Agnostic Saliency Estimation

STeP-Diff: Spatio-Temporal Physics-Informed Diffusion Models for Mobile Fine-Grained Pollution Forecasting

AutoGuard: A Self-Healing Proactive Security Layer for DevSecOps Pipelines Using Reinforcement Learning

Mitigating Object and Action Hallucinations in Multimodal LLMs via Self-Augmented Contrastive Alignment

Counting Without Running: Evaluating LLMs' Reasoning About Code Complexity

RGE-GCN: Recursive Gene Elimination with Graph Convolutional Networks for RNA-seq based Early Cancer Detection

DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle

Bayes-DIC Net: Estimating Digital Image Correlation Uncertainty with Bayesian Neural Networks

MANTRA: a Framework for Multi-stage Adaptive Noise TReAtment During Training

Evaluating Long-Context Reasoning in LLM-Based WebAgents

Gamma-from-Mono: Road-Relative, Metric, Self-Supervised Monocular Geometry for Vehicular Applications

Learning Single-Image Super-Resolution in the JPEG Compressed Domain

Bootstrapped Mixed Rewards for RL Post-Training: Injecting Canonical Action Order

Quantitative Analysis of Technical Debt and Pattern Violation in Large Language Model Architectures

The Initialization Determines Whether In-Context Learning Is Gradient Descent

Catching UX Flaws in Code: Leveraging LLMs to Identify Usability Flaws at the Development Stage

Hey GPT-OSS, Looks Like You Got It - Now Walk Me Through It! An Assessment of the Reasoning Language Models Chain of Thought Mechanism for Digital Forensics

Fine-Tuning ChemBERTa for Predicting Inhibitory Activity Against TDP1 Using Deep Learning

MVRoom: Controllable 3D Indoor Scene Generation with Multi-View Diffusion Models

CRAFT-E: A Neuro-Symbolic Framework for Embodied Affordance Grounding

Machine Phenomenology: A Simple Equation Classifying Fast Radio Bursts

Network of Theseus (like the ship)

BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training

OnSight Pathology: A real-time platform-agnostic computational pathology companion for histopathology

From FLOPs to Footprints: The Resource Cost of Artificial Intelligence

Artificial Intelligence / Human Intelligence: Who Controls Whom?

When AI Takes the Couch: Psychometric Jailbreaks Reveal Internal Conflict in Frontier Models

Measuring Agents in Production

Can machines perform a qualitative data analysis? Reading the debate with Alan Turing

Towards Contextual Sensitive Data Detection

Humanity in the Age of AI: Reassessing 2025's Existential-Risk Narratives

Artificial Intelligence Competence of K-12 Students Shapes Their AI Risk Perception: A Co-occurrence Network Analysis

AI-Enabled grading with near-domain data for scaling feedback with human-level accuracy

MindFuse: Towards GenAI Explainability in Marketing Strategy Co-Creation

HAI-Eval: Measuring Human-AI Synergy in Collaborative Coding

Responsible LLM Deployment for High-Stake Decisions by Decentralized Technologies and Human-AI Interactions

Rethinking AI Evaluation in Education: The TEACH-AI Framework and Benchmark for Generative AI Assistants

Retrieval-Augmented Few-Shot Prompting Versus Fine-Tuning for Code Vulnerability Detection

LegalWebAgent: Empowering Access to Justice via LLM-Based Web Agents

ReVeal-MT: A Physics-Informed Neural Network for Multi-Transmitter Radio Environment Mapping

Partial multivariate transformer as a tool for cryptocurrencies time series prediction

MultiGA: Leveraging Multi-Source Seeding in Genetic Algorithms

Memory-DD: A Low-Complexity Dendrite-Inspired Neuron for Temporal Prediction Tasks

The changing surface of the world's roads

Constant-Time Motion Planning with Manipulation Behaviors

Created by

Haebom

Category

Empty

저자

Nayesha Gandotra, Itamar Mishani, Maxim Likhachev

개요

B-CTMP (Behavioral Constant-Time Motion Planner)는 안전성, 효율성, 신뢰성을 보장하는 로봇 조작을 위한 알고리즘이다. CTMP를 확장하여 두 단계의 조작 작업(충돌 없는 동작과 조작 수행)을 해결하며, 미리 계산된 데이터를 활용하여 짧은 시간 안에 쿼리를 처리한다. 시뮬레이션 및 실제 로봇 실험을 통해 쉘프에서 물건 꺼내기 및 플러그 삽입과 같은 작업을 성공적으로 수행함을 입증했다.

시사점, 한계점

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시사점:

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충돌 없는 계획과 물체 조작을 단일 프레임워크 내에서 통합하여 빠른 속도와 성공률을 보장한다.

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반 구조화된 환경에서의 로봇 조작에 대한 속도와 성공을 보장한다.

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실시간 환경에서 실행 가능한 조작 계획을 가능하게 한다.

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한계점:

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CTMP의 한계를 공유할 수 있음.

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복잡한 환경에서의 적용 가능성은 추가 연구가 필요함.

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구체적인 작업에 대한 적합성은 추가적인 테스트가 필요함.

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