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.

CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

Ada-TransGNN: An Air Quality Prediction Model Based On Adaptive Graph Convolutional Networks

Unlearning as Ablation: Toward a Falsifiable Benchmark for Generative Scientific Discovery

Consistent Opponent Modeling of Static Opponents in Imperfect-Information Games

Finding Outliers in a Haystack: Anomaly Detection for Large Pointcloud Scenes

Agentic AI for Software: thoughts from Software Engineering community

Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs

Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning

Dream to Chat: Model-based Reinforcement Learning on Dialogues with User Belief Modeling

A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems

Generative Artificial Intelligence and Agents in Research and Teaching

CALR: Corrective Adaptive Low-Rank Decomposition for Efficient Large Language Model Layer Compression

Comparative Analysis of UAV Path Planning Algorithms for Efficient Navigation in Urban 3D Environments

Retrieval Enhanced Feedback via In-context Neural Error-book

From Confidence to Collapse in LLM Factual Robustness

On Task Vectors and Gradients

Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model

DLLMQuant: Quantizing Diffusion-based Large Language Models

LLM-Enhanced Linear Autoencoders for Recommendation

Leveraging GNN to Enhance MEF Method in Predicting ENSO

Uncertainty-Guided Face Matting for Occlusion-Aware Face Transformation

New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants

Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems

SKA-Bench: A Fine-Grained Benchmark for Evaluating Structured Knowledge Understanding of LLMs

Apple Intelligence Foundation Language Models: Tech Report 2025

SE-VLN: A Self-Evolving Vision-Language Navigation Framework Based on Multimodal Large Language Models

Demographic-aware fine-grained classification of pediatric wrist fractures

Krul: Efficient State Restoration for Multi-turn Conversations with Dynamic Cross-layer KV Sharing

Solar Altitude Guided Scene Illumination

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning

Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models

EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion

RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection

Revisiting SSL for sound event detection: complementary fusion and adaptive post-processing

Concept-Guided Interpretability via Neural Chunking

Unveiling the Landscape of LLM Deployment in the Wild: An Empirical Study

An Ontology-Driven Graph RAG for Legal Norms: A Hierarchical, Temporal, and Deterministic Approach

Prefill-level Jailbreak: A Black-Box Risk Analysis of Large Language Models

Video CLIP Model for Multi-View Echocardiography Interpretation

A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Disease Detection from Retinal Fundus Images

M$^2$IV: Towards Efficient and Fine-grained Multimodal In-Context Learning via Representation Engineering

Noise-based reward-modulated learning

Faster Parameter-Efficient Tuning with Token Redundancy Reduction

UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials

Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems

Large Language Models Badly Generalize across Option Length, Problem Types, and Irrelevant Noun Replacements

TableTalk: Scaffolding Spreadsheet Development with a Language Agent

StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis

Generative Artificial Intelligence-Supported Pentesting: A Comparison between Claude Opus, GPT-4, and Copilot

Safe Multiagent Coordination via Entropic Exploration

TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use

Cultural Dimensions of AI Perception: Charting Expectations, Risks, Benefits, Tradeoffs, and Value in Germany and China

CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers

Perception Gaps in Risk, Benefit, and Value Between Experts and Public Challenge Socially Accepted AI

Hierarchical Object-Oriented POMDP Planning for Object Rearrangement

From Intents to Conversations: Generating Intent-Driven Dialogues with Contrastive Learning for Multi-Turn Classification

Secure Reinforcement Learning via Shuffle Privacy Model

Overcoming label shift with target-aware federated learning

Benchmarking XAI Explanations with Human-Aligned Evaluations

HonestCyberEval: An AI Cyber Risk Benchmark for Automated Software Exploitation

Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning

GeNet: A Multimodal LLM-Based Co-Pilot for Network Topology and Configuration

ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context

Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL

Exploring the Robustness of Language Models for Tabular Question Answering via Attention Analysis

Learning county from pixels: corn yield prediction with attention-weighted multiple instance learning

Memory augment is All You Need for image restoration

Rethinking Distribution Shifts: Empirical Analysis and Inductive Modeling for Tabular Data

DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models

Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

ST-Raptor: LLM-Powered Semi-Structured Table Question Answering

Route-and-Execute: Auditable Model-Card Matching and Specialty-Level Deployment

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

Response and Prompt Evaluation to Prevent Parasocial Relationships with Chatbots

Profile-Aware Maneuvering: A Dynamic Multi-Agent System for Robust GAIA Problem Solving by AWorld

Multi-Agent LLMs as Ethics Advocates for AI-Based Systems

Feature-Guided Neighbor Selection for Non-Expert Evaluation of Model Predictions

Architecting Clinical Collaboration: Multi-Agent Reasoning Systems for Multimodal Medical VQA

mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation

Jigsaw-Puzzles: From Seeing to Understanding to Reasoning in Vision-Language Models

The Influence of Human-inspired Agentic Sophistication in LLM-driven Strategic Reasoners

YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models

Consensus in Motion: A Case of Dynamic Rationality of Sequential Learning in Probability Aggregation

Can Large Language Models Act as Ensembler for Multi-GNNs?

Pessimistic Iterative Planning with RNNs for Robust POMDPs

Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding

Integrating Large Language Model for Improved Causal Discovery

A Survey on Causal Discovery: Theory and Practice

Generative Interfaces for Language Models

Interpolating Speaker Identities in Embedding Space for Data Expansion

VibeVoice Technical Report

LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding

Understanding Tool-Integrated Reasoning

Emotions as Ambiguity-aware Ordinal Representations

Real-Time Model Checking for Closed-Loop Robot Reactive Planning

Profile-Aware Maneuvering: A Dynamic Multi-Agent System for Robust GAIA Problem Solving by AWorld

Created by

Haebom

저자

Zhitian Xie, Qintong Wu, Chengyue Yu, Chenyi Zhuang, Jinjie Gu

개요

본 논문은 대규모 언어 모델(LLM) 기반 지능형 에이전트가 외부 도구를 활용하여 복잡한 실제 문제를 해결하는 과정에서 발생하는 신뢰성 문제를 해결하기 위해, AWorld 프레임워크 내에서 실행 에이전트와 감시 에이전트로 구성된 동적 다중 에이전트 시스템(MAS)을 제안합니다. 특히, 제어 이론의 시스템 식별에서 영감을 받은 방법론을 통해 실행 에이전트의 성능 프로파일을 생성하고, 이를 기반으로 감시 에이전트가 에이전트의 고유한 약점에 맞춰 목표 지향적인 개입을 수행하여 시스템의 강건성을 향상시킵니다. GAIA 데이터셋을 이용한 실험 결과, 제안된 프로파일 인식 MAS는 단일 에이전트 시스템 및 일반적인 감시 시스템보다 효율성과 안정성이 훨씬 뛰어나며, GAIA 리더보드에서 오픈소스 프로젝트 중 1위를 달성했습니다. 이는 신뢰할 수 있는 지능형 시스템 구축에는 에이전트 간의 협업뿐 아니라 각 에이전트의 고유한 능력과 한계에 대한 경험적 이해가 필수적임을 보여줍니다.

시사점, 한계점

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시사점:

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다중 에이전트 시스템을 통해 LLM 기반 지능형 에이전트의 신뢰성 문제 해결 가능성 제시.

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제어 이론 기반의 시스템 식별 방법론을 활용한 프로파일 인식 감시는 효율적이고 안정적인 시스템 운영에 기여.

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GAIA 리더보드 1위 달성을 통해 제안된 시스템의 우수성 검증.

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신뢰할 수 있는 지능형 시스템 구축을 위한 새로운 패러다임 제시 (에이전트의 능력과 한계에 대한 깊이 있는 이해 필요성 강조).

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한계점:

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제안된 시스템의 성능은 특정 데이터셋(GAIA)에 대한 결과이며, 다른 데이터셋이나 작업에 대한 일반화 가능성은 추가 연구 필요.

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시스템 식별 과정에 필요한 오프라인 학습 데이터의 규모 및 질에 대한 의존성 존재.

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프로파일 인식 감시의 복잡성 증가로 인한 계산 비용 증가 가능성.

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실제 세계의 복잡하고 다양한 상황에 대한 적용 가능성 및 일반화에 대한 추가적인 검증 필요.

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