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전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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IG Parser: A Software Package for the Encoding of Institutional Statements using the Institutional Grammar

One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling

J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization

Evaluating the efficacy of LLM Safety Solutions : The Palit Benchmark Dataset

From Assistants to Adversaries: Exploring the Security Risks of Mobile LLM Agents

Leveraging LLM Inconsistency to Boost Pass@k Performance

Sinusoidal Initialization, Time for a New Start

Enhancing Channel-Independent Time Series Forecasting via Cross-Variate Patch Embedding

Any-to-Any Learning in Computational Pathology via Triplet Multimodal Pretraining

Predicting Turn-Taking and Backchannel in Human-Machine Conversations Using Linguistic, Acoustic, and Visual Signals

ChromFound: Towards A Universal Foundation Model for Single-Cell Chromatin Accessibility Data

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems

RoboFAC: A Comprehensive Framework for Robotic Failure Analysis and Correction

LLM-DSE: Searching Accelerator Parameters with LLM Agents

Online Iterative Self-Alignment for Radiology Report Generation

Reachability Barrier Networks: Learning Hamilton-Jacobi Solutions for Smooth and Flexible Control Barrier Functions

Improving Medium Range Severe Weather Prediction through Transformer Post-processing of AI Weather Forecasts

BioCube: A Multimodal Dataset for Biodiversity Research

One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems

TCC-Bench: Benchmarking the Traditional Chinese Culture Understanding Capabilities of MLLMs

FALCON: False-Negative Aware Learning of Contrastive Negatives in Vision-Language Pretraining

GRoQ-Loco: Generalist and Robot-agnostic Quadruped Locomotion Control using Offline Datasets

Who You Are Matters: Bridging Topics and Social Roles via LLM-Enhanced Logical Recommendation

Artificial Intelligence Bias on English Language Learners in Automatic Scoring

Learning Long-Context Diffusion Policies via Past-Token Prediction

Fast Text-to-Audio Generation with Adversarial Post-Training

Unified Continuous Generative Models

Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?

Technical Report: Quantifying and Analyzing the Generalization Power of a DNN

Prompting Large Language Models for Training-Free Non-Intrusive Load Monitoring

On-Device LLM for Context-Aware Wi-Fi Roaming

Efficient Fine-Tuning of Quantized Models via Adaptive Rank and Bitwidth

Understanding University Students' Use of Generative AI: The Roles of Demographics and Personality Traits

Adaptive Thinking via Mode Policy Optimization for Social Language Agents

LLM-hRIC: LLM-empowered Hierarchical RAN Intelligent Control for O-RAN

On the Boolean Network Theory of Datalog$^\neg$

Learning to Reason under Off-Policy Guidance

How Effective Can Dropout Be in Multiple Instance Learning ?

Learning Joint ID-Textual Representation for ID-Preserving Image Synthesis

Walk the Talk? Measuring the Faithfulness of Large Language Model Explanations

Cross-Document Cross-Lingual NLI via RST-Enhanced Graph Fusion and Interpretability Prediction

S1-Bench: A Simple Benchmark for Evaluating System 1 Thinking Capability of Large Reasoning Models

Beyond Self-Reports: Multi-Observer Agents for Personality Assessment in Large Language Models

Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation

Scaling Test-Time Inference with Policy-Optimized, Dynamic Retrieval-Augmented Generation via KV Caching and Decoding

Breaking Language Barriers in Visual Language Models via Multilingual Textual Regularization

LogicQA: Logical Anomaly Detection with Vision Language Model Generated Questions

Conjuring Positive Pairs for Efficient Unification of Representation Learning and Image Synthesis

CRCE: Coreference-Retention Concept Erasure in Text-to-Image Diffusion Models

LED: LLM Enhanced Open-Vocabulary Object Detection without Human Curated Data Generation

MirrorShield: Towards Universal Defense Against Jailbreaks via Entropy-Guided Mirror Crafting

HICD: Hallucination-Inducing via Attention Dispersion for Contrastive Decoding to Mitigate Hallucinations in Large Language Models

RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs

Language Models, Graph Searching, and Supervision Adulteration: When More Supervision is Less and How to Make More More

Cost-Optimal Grouped-Query Attention for Long-Context Modeling

Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation

On the Vulnerability of Concept Erasure in Diffusion Models

Char-mander Use mBackdoor! A Study of Cross-lingual Backdoor Attacks in Multilingual LLMs

SQLong: Enhanced NL2SQL for Longer Contexts with LLMs

DiffSampling: Enhancing Diversity and Accuracy in Neural Text Generation

TreeCut: A Synthetic Unanswerable Math Word Problem Dataset for LLM Hallucination Evaluation

Attention Mechanism for LLM-based Agents Dynamic Diffusion under Information Asymmetry

Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection

R2-KG: General-Purpose Dual-Agent Framework for Reliable Reasoning on Knowledge Graphs

DeepResonance: Enhancing Multimodal Music Understanding via Music-centric Multi-way Instruction Tuning

MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval

EquiBench: Benchmarking Large Language Models' Understanding of Program Semantics via Equivalence Checking

EssayJudge: A Multi-Granular Benchmark for Assessing Automated Essay Scoring Capabilities of Multimodal Large Language Models

Uncovering Untapped Potential in Sample-Efficient World Model Agents

MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language Models

CoLA: Compute-Efficient Pre-Training of LLMs via Low-Rank Activation

AI-driven Personalized Privacy Assistants: a Systematic Literature Review

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer

Online Scheduling for LLM Inference with KV Cache Constraints

Uni-Retrieval: A Multi-Style Retrieval Framework for STEM's Education

Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation

Latent Action Learning Requires Supervision in the Presence of Distractors

Redefining Machine Unlearning: A Conformal Prediction-Motivated Approach

On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning

People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text

NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations

MMDocIR: Benchmarking Multi-Modal Retrieval for Long Documents

Building Symbiotic AI: Reviewing the AI Act for a Human-Centred, Principle-Based Framework

TiEBe: Tracking Language Model Recall of Notable Worldwide Events Through Time

xLSTM-SENet: xLSTM for Single-Channel Speech Enhancement

A Separable Self-attention Inspired by the State Space Model for Computer Vision

Cross-model Transferability among Large Language Models on the Platonic Representations of Concepts

KunServe: Efficient Parameter-centric Memory Management for LLM Serving

Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension

Can LLMs be Good Graph Judge for Knowledge Graph Construction?

RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrations

Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language Models

Knowledge-Guided Prompt Learning for Request Quality Assurance in Public Code Review

Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study

M-RewardBench: Evaluating Reward Models in Multilingual Settings

Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillation

RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals

Bayes Adaptive Monte Carlo Tree Search for Offline Model-based Reinforcement Learning

Large Continual Instruction Assistant

TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems

Created by

Haebom

저자

Liwen Wang, Wenxuan Wang, Shuai Wang, Zongjie Li, Zhenlan Ji, Zongyi Lyu, Daoyuan Wu, Shing-Chi Cheung

개요

본 논문은 대규모 언어 모델(LLM) 기반 다중 에이전트 시스템(MAS)의 지적 재산(IP) 보호 취약성을 다룬다. 연구진은 MAS의 공개 API만을 이용하여 시스템 아키텍처, 프롬프트, 작업 지시사항, 도구 사용 등 민감한 정보를 추출하는 새로운 공격 프레임워크인 MASLEAK을 제시한다. MASLEAK은 컴퓨터 웜의 전파 방식에서 영감을 얻어, 적대적 질의(query)를 통해 각 에이전트의 응답을 유도하고 전파하여 시스템의 내부 정보를 획득한다. 810개의 합성 MAS 애플리케이션 데이터셋과 Coze, CrewAI와 같은 실제 애플리케이션을 대상으로 실험한 결과, 시스템 프롬프트 및 작업 지시사항은 평균 87%, 시스템 아키텍처는 대부분의 경우 92%의 높은 정확도로 정보 추출에 성공했다.

시사점, 한계점

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시사점:

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LLM 기반 MAS의 IP 보호 취약성을 체계적으로 분석하고, 실질적인 공격 위협을 제시한다.

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MASLEAK은 실제 환경에서 효과적으로 작동하는 실용적인 공격 프레임워크임을 보여준다.

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LLM 기반 MAS 개발 및 운영 시 IP 보호를 위한 새로운 보안 메커니즘 개발의 필요성을 강조한다.

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한계점:

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MASLEAK의 효과는 특정 유형의 MAS 아키텍처 및 API 설계에 의존할 수 있다.

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실제 세계의 모든 MAS 애플리케이션에 대해 일반화 가능성을 보장하기 어렵다.

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MASLEAK에 대한 방어 메커니즘 개발 및 평가에 대한 추가 연구가 필요하다.

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