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.

Boundary-Guided Policy Optimization for Memory-efficient RL of Diffusion Large Language Models

ManiAgent: An Agentic Framework for General Robotic Manipulation

AndesVL Technical Report: An Efficient Mobile-side Multimodal Large Language Model

ParsVoice: A Large-Scale Multi-Speaker Persian Speech Corpus for Text-to-Speech Synthesis

Optimally Deep Networks -- Adapting Model Depth to Datasets for Superior Efficiency

BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions

AGENTIQL: An Agent-Inspired Multi-Expert Framework for Text-to-SQL Generation

Towards Safe Maneuvering of Double-Ackermann-Steering Robots with a Soft Actor-Critic Framework

The Algorithmic Regulator

HccePose(BF): Predicting Front & Back Surfaces to Construct Ultra-Dense 2D-3D Correspondences for Pose Estimation

ICL-Router: In-Context Learned Model Representations for LLM Routing

CrisiText: A dataset of warning messages for LLM training in emergency communication

GTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection (Preprint)

Scalable Policy-Based RL Algorithms for POMDPs

OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain

AgentBuilder: Exploring Scaffolds for Prototyping User Experiences of Interface Agents

Neon: Negative Extrapolation From Self-Training Improves Image Generation

Triplet-Structured Knowledge Integration for Multi-Turn Medical Reasoning

General Exploratory Bonus for Optimistic Exploration in RLHF

PolySim: Bridging the Sim-to-Real Gap for Humanoid Control via Multi-Simulator Dynamics Randomization

Asymmetric Proximal Policy Optimization: mini-critics boost LLM reasoning

Graph2Eval: Automatic Multimodal Task Generation for Agents via Knowledge Graphs

Understanding Language Prior of LVLMs by Contrasting Chain-of-Embedding

Large language models management of medications: three performance analyses

Responsible AI Technical Report

A Longitudinal Randomized Control Study of Companion Chatbot Use: Anthropomorphism and Its Mediating Role on Social Impacts

SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer

TISDiSS: A Training-Time and Inference-Time Scalable Framework for Discriminative Source Separation

Efficient and Versatile Model for Multilingual Information Retrieval of Islamic Text: Development and Deployment in Real-World Scenarios

StegOT: Trade-offs in Steganography via Optimal Transport

General Demographic Foundation Models for Enhancing Predictive Performance Across Diseases and Populations

Attention as an Adaptive Filter

Diffusion Language Models Know the Answer Before Decoding

NinA: Normalizing Flows in Action. Training VLA Models with Normalizing Flows

Hard Examples Are All You Need: Maximizing GRPO Post-Training Under Annotation Budgets

AdaptJobRec: Enhancing Conversational Career Recommendation through an LLM-Powered Agentic System

An Introduction to Sliced Optimal Transport

EMSEdit: Efficient Multi-Step Meta-Learning-based Model Editing

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

mmWave Radar-Based Non-Line-of-Sight Pedestrian Localization at T-Junctions Utilizing Road Layout Extraction via Camera

Capturing More: Learning Multi-Domain Representations for Robust Online Handwriting Verification

A Cooperative Approach for Knowledge-based Business Process Design in a Public Authority

Finding Dori: Memorization in Text-to-Image Diffusion Models Is Not Local

Feature Distillation is the Better Choice for Model-Heterogeneous Federated Learning

Knowledge Fusion via Bidirectional Information Aggregation

LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop

Dual Perspectives on Non-Contrastive Self-Supervised Learning

SAFER: Probing Safety in Reward Models with Sparse Autoencoder

Inverse Design in Nanophotonics via Representation Learning

SPADE: Spatial Transcriptomics and Pathology Alignment Using a Mixture of Data Experts for an Expressive Latent Space

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents

Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate Time Series

BridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language Models

Uncertainty Estimation on Graphs with Structure Informed Stochastic Partial Differential Equations

EvolveNav: Empowering LLM-Based Vision-Language Navigation via Self-Improving Embodied Reasoning

Can LLMs Reason Structurally? An Evaluation via the Lens of Data Structures

Finite Sample Analysis of Linear Temporal Difference Learning with Arbitrary Features

Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models

Protein Design with Dynamic Protein Vocabulary

Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator

Steering Large Language Models for Machine Translation Personalization

AsynFusion: Towards Asynchronous Latent Consistency Models for Decoupled Whole-Body Audio-Driven Avatars

Joint Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self Supervised Learning

Fixed Point Explainability

Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarking

MobileCity: An Efficient Framework for Large-Scale Urban Behavior Simulation

A Customized SAT-based Solver for Graph Coloring

Multi-Agent Autonomous Driving Systems with Large Language Models: A Survey of Recent Advances

FOCUS on Contamination: A Geospatial Deep Learning Framework with a Noise-Aware Loss for Surface Water PFAS Prediction

ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization

Query Brand Entity Linking in E-Commerce Search

AgentBreeder: Mitigating the AI Safety Risks of Multi-Agent Scaffolds via Self-Improvement

GraphRAG under Fire

Polynomial-Time Algorithms for Fair Orientations of Chores

CiteBART: Learning to Generate Citations for Local Citation Recommendation

Reframing Image Difference Captioning with BLIP2IDC and Synthetic Augmentation

Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds

COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences

Generative AI for Requirements Engineering: A Systematic Literature Review

Assessing Latency in ASR Systems: A Methodological Perspective for Real-Time Use

ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training

Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions

Offline Fictitious Self-Play for Competitive Games

When "Competency" in Reasoning Opens the Door to Vulnerability: Jailbreaking LLMs via Novel Complex Ciphers

Can ChatGPT support software verification?

Optimized Layerwise Approximation for Efficient Private Inference on Fully Homomorphic Encryption

DRIFT: Decompose, Retrieve, Illustrate, then Formalize Theorems

Adaptive Dual Reasoner: Large Reasoning Models Can Think Efficiently by Hybrid Reasoning

Concise Reasoning in the Lens of Lagrangian Optimization

Humanoid Artificial Consciousness Designed with Large Language Model Based on Psychoanalysis and Personality Theory

TripScore: Benchmarking and rewarding real-world travel planning with fine-grained evaluation

Agent Learning via Early Experience

L2M-AID: Autonomous Cyber-Physical Defense by Fusing Semantic Reasoning of Large Language Models with Multi-Agent Reinforcement Learning (Preprint)

Clean First, Align Later: Benchmarking Preference Data Cleaning for Reliable LLM Alignment

Similarity Field Theory: A Mathematical Framework for Intelligence

Large Language Models in Operations Research: Methods, Applications, and Challenges

MoEs Are Stronger than You Think: Hyper-Parallel Inference Scaling with RoE

Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining

MapAgent: A Hierarchical Agent for Geospatial Reasoning with Dynamic Map Tool Integration

Generative AI for Requirements Engineering: A Systematic Literature Review

Created by

Haebom

저자

Haowei Cheng, Jati H. Husen, Yijun Lu, Teeradaj Racharak, Nobukazu Yoshioka, Naoyasu Ubayashi, Hironori Washizaki

GenAI 기반 요구사항 공학 연구의 체계적 검토

개요

본 연구는 점점 더 복잡해지는 소프트웨어 시스템을 처리하는 데 있어 요구사항 공학(RE)이 직면한 과제를 해결하기 위한 생성형 AI(GenAI)의 활용을 조사합니다. GenAI 기반 RE에 대한 체계적인 분석이 부족하다는 점을 고려하여, 2019년부터 2025년까지 주요 학술 데이터베이스에서 발표된 238편의 논문을 대상으로 동향, 방법론, 과제 및 향후 방향에 초점을 맞춰 관련 연구를 검토합니다. 현재 응용 프로그램에서는 생성형 사전 훈련 변환기 모델이 지배적이며, 분석 및 추출 단계에 가장 많은 관심이 집중되어 있지만, 관리 단계는 충분히 탐구되지 않았습니다.

시사점, 한계점

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생성형 사전 훈련 변환기 모델이 현재 응용 분야에서 지배적입니다.

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분석 및 추출 단계에 가장 많은 관심이 집중되어 있습니다.

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관리 단계는 연구가 부족합니다.

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재현성, 환각, 해석 가능성이 상호 연관된 핵심 과제로 나타났습니다.

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산업 적용은 아직 초기 단계이며, 생산 수준의 통합은 매우 적습니다.

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평가 방법의 성숙도 격차, 제한된 도구 및 데이터 세트 가용성, 파편화된 벤치마킹 접근 방식이 존재합니다.

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핵심 과제 간의 강한 상관 관계는 상호 의존성을 목표로 하는 전문화된 아키텍처의 필요성을 시사합니다.

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제한된 배포는 일반화 가능성, 데이터 품질 및 확장 가능한 평가 방법의 병목 현상을 반영합니다.

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성공적인 도입을 위해서는 기술적 강건성, 방법론적 성숙도 및 거버넌스 통합에 대한 조정된 개발이 필요합니다.

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