Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

OPTIC-ER: A Reinforcement Learning Framework for Real-Time Emergency Response and Equitable Resource Allocation in Underserved African Communities

BioAnalyst: A Foundation Model for Biodiversity

Scaling Towards the Information Boundary of Instruction Sets: The Infinity Instruct Subject Technical Report

Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations

NeuroPhysNet: A FitzHugh-Nagumo-Based Physics-Informed Neural Network Framework for Electroencephalograph (EEG) Analysis and Motor Imagery Classification

PRO-V-R1: Reasoning Enhanced Programming Agent for RTL Verification

Large language models can learn and generalize steganographic chain-of-thought under process supervision

Turing Test 2.0: The General Intelligence Threshold

Consistency-based Abductive Reasoning over Perceptual Errors of Multiple Pre-trained Models in Novel Environments

Empowering Clients - Transformation of Design Processes Due to Generative AI

The Delusional Hedge Algorithm as a Model of Human Learning from Diverse Opinions

The Universal Weight Subspace Hypothesis

DraCo: Draft as CoT for Text-to-Image Preview and Rare Concept Generation

ShadowDraw: From Any Object to Shadow-Drawing Compositional Art

Semantic Soft Bootstrapping: Long Context Reasoning in LLMs without Reinforcement Learning

TV2TV: A Unified Framework for Interleaved Language and Video Generation

Structured Document Translation via Format Reinforcement Learning

SA-IQA: Redefining Image Quality Assessment for Spatial Aesthetics with Multi-Dimensional Rewards

David vs. Goliath: Can Small Models Win Big with Agentic AI in Hardware Design?

Multi-LLM Collaboration for Medication Recommendation

Meta-Learning for Quantum Optimization via Quantum Sequence Model

QKAN-LSTM: Quantum-inspired Kolmogorov-Arnold Long Short-term Memory

Arbitrage: Efficient Reasoning via Advantage-Aware Speculation

Model-Free Assessment of Simulator Fidelity via Quantile Curves

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

Jr. AI Scientist and Its Risk Report: Autonomous Scientific Exploration from a Baseline Paper

Created by

Haebom

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저자

Atsuyuki Miyai, Mashiro Toyooka, Takashi Otonari, Zaiying Zhao, Kiyoharu Aizawa

개요

본 논문은 신뢰할 수 있고 지속 가능한 AI 기반 과학 발전을 보장하고 학술 생태계의 무결성을 유지하기 위해 AI 과학자 시스템의 현재 기능과 위험을 이해하는 데 중점을 둡니다. 이를 위해, 초보 학생 연구자의 핵심 연구 워크플로우를 모방하는 최첨단 자율 AI 과학자 시스템인 Jr. AI Scientist를 개발했습니다. Jr. AI Scientist는 인간 멘토의 기본 논문을 바탕으로, 한계를 분석하고, 개선을 위한 새로운 가설을 세우고, 개선이 실현될 때까지 반복적으로 실험을 수행하며, 결과를 담은 논문을 작성합니다. Jr. AI Scientist는 완전 자동화를 가정하거나 소규모 코드에서 작동하는 이전 접근 방식과 달리, 잘 정의된 연구 워크플로우를 따르고 복잡한 멀티 파일 구현을 처리하기 위해 최신 코딩 에이전트를 활용하여 과학적으로 가치 있는 기여를 합니다. Jr. AI Scientist는 실제 NeurIPS, IJCV 및 ICLR 논문을 기반으로 새로운 방법론을 제안하고 구현하여 새로운 연구 논문을 성공적으로 생성했습니다. 평가는 AI 리뷰어, 저자 주도 평가 및 AI 기반 과학적 기여를 위한 장소인 Agents4Science에의 제출을 통해 수행되었습니다. 연구 결과는 Jr. AI Scientist가 기존의 완전 자동화 시스템보다 높은 리뷰 점수를 받는 논문을 생성함을 보여줍니다.

시사점, 한계점

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Jr. AI Scientist는 실제 연구 논문을 기반으로 새로운 연구 논문을 성공적으로 생성하고, 기존 자동화 시스템보다 높은 리뷰 점수를 받았습니다.

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Jr. AI Scientist는 복잡한 멀티 파일 구현을 처리하기 위해 최신 코딩 에이전트를 활용하여 과학적 가치를 창출했습니다.

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저자 평가 및 Agents4Science 리뷰를 통해 현재 AI Scientist 시스템의 잠재적 위험과 미래 연구의 주요 과제를 파악했습니다.

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개발 과정에서 다양한 위험 요소를 확인하고 보고했습니다.

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AI Scientist 시스템의 현재 역할과 한계를 명확히 하고, 인간 전문 지식이 여전히 필요한 영역과 시스템 발전과 함께 나타날 수 있는 위험에 대한 통찰력을 제공합니다.

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