Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
본 페이지는 Google Gemini를 활용해 요약 정리하며, 비영리로 운영 됩니다.
논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models

Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model

The Dark Side of LLMs: Agent-based Attacks for Complete Computer Takeover

Artificial Generals Intelligence: Mastering Generals.io with Reinforcement Learning

HeLo: Heterogeneous Multi-Modal Fusion with Label Correlation for Emotion Distribution Learning

ixi-GEN: Efficient Industrial sLLMs through Domain Adaptive Continual Pretraining

Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications

PWD: Prior-Guided and Wavelet-Enhanced Diffusion Model for Limited-Angle CT

VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting

Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision

Multi-modal Representations for Fine-grained Multi-label Critical View of Safety Recognition

MCFormer: A Multi-Cost-Volume Network and Comprehensive Benchmark for Particle Image Velocimetry

Toward Efficient Speech Emotion Recognition via Spectral Learning and Attention

Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards

Solving the Hubbard model with Neural Quantum States

S2FGL: Spatial Spectral Federated Graph Learning

Beyond Spatial Frequency: Pixel-wise Temporal Frequency-based Deepfake Video Detection

Are Vision Transformer Representations Semantically Meaningful? A Case Study in Medical Imaging

Description of the Training Process of Neural Networks via Ergodic Theorem : Ghost nodes

A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search

Damba-ST: Domain-Adaptive Mamba for Efficient Urban Spatio-Temporal Prediction

Studying and Improving Graph Neural Network-based Motif Estimation

Learning Algorithms in the Limit

Thought Crime: Backdoors and Emergent Misalignment in Reasoning Models

HadaNorm: Diffusion Transformer Quantization through Mean-Centered Transformations

MAEBE: Multi-Agent Emergent Behavior Framework

Evaluating LLM Agent Adherence to Hierarchical Safety Principles: A Lightweight Benchmark for Probing Foundational Controllability Components

What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training

From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?

One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory

BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems

Anchoring AI Capabilities in Market Valuations: The Capability Realization Rate Model and Valuation Misalignment Risk

Fair Uncertainty Quantification for Depression Prediction

MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework

A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning

Constraint Programming Models For Serial Batch Scheduling With Minimum Batch Size

Toward Holistic Evaluation of Recommender Systems Powered by Generative Models

Rankers, Judges, and Assistants: Towards Understanding the Interplay of LLMs in Information Retrieval Evaluation

Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank Adaptation

Decoding AI Judgment: How LLMs Assess News Credibility and Bias

Ethical Concerns of Generative AI and Mitigation Strategies: A Systematic Mapping Study

Diffusion Augmented Retrieval: A Training-Free Approach to Interactive Text-to-Image Retrieval

Derivation of Output Correlation Inferences for Multi-Output (aka Multi-Task) Gaussian Process

Cosmos World Foundation Model Platform for Physical AI

Enhancing Transformers for Generalizable First-Order Logical Entailment

Multi-Scenario Reasoning: Unlocking Cognitive Autonomy in Humanoid Robots for Multimodal Understanding

DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and Trustworthiness

Tiny-Align: Bridging Automatic Speech Recognition and Large Language Model on the Edge

Understanding Chain-of-Thought in LLMs through Information Theory

A Multi-Granularity Supervised Contrastive Framework for Remaining Useful Life Prediction of Aero-engines

MarineFormer: A Spatio-Temporal Attention Model for USV Navigation in Dynamic Marine Environments

HARMONIC: Cognitive and Control Collaboration in Human-Robotic Teams

Investigating Context-Faithfulness in Large Language Models: The Roles of Memory Strength and Evidence Style

Masked Image Modeling: A Survey

Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences

Curriculum Negative Mining For Temporal Networks

C3T: Cross-modal Transfer Through Time for Sensor-based Human Activity Recognition

Multi-Head RAG: Solving Multi-Aspect Problems with LLMs

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

Offline Trajectory Optimization for Offline Reinforcement Learning

Structure Guided Large Language Model for SQL Generation

A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptive

Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning

Unsupervised Automata Learning via Discrete Optimization

Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series

An Algorithm for Learning Smaller Representations of Models With Scarce Data

GTA1: GUI Test-time Scaling Agent

Fuzzy Classification Aggregation for a Continuum of Agents

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift

Establishing Best Practices for Building Rigorous Agentic Benchmarks

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

AI's Euclid's Elements Moment: From Language Models to Computable Thought

Closer to Language than Steam: AI as the Cognitive Engine of a New Productivity Revolution

Access Controls Will Solve the Dual-Use Dilemma

Task Assignment and Exploration Optimization for Low Altitude UAV Rescue via Generative AI Enhanced Multi-agent Reinforcement Learning

Affordable AI Assistants with Knowledge Graph of Thoughts

Deontic Temporal Logic for Formal Verification of AI Ethics

Multi-Agent Pathfinding Under Team-Connected Communication Constraint via Adaptive Path Expansion and Dynamic Leading

Constrain Alignment with Sparse Autoencoders

Multi-modal Generative AI: Multi-modal LLMs, Diffusions and the Unification

SimSUM: Simulated Benchmark with Structured and Unstructured Medical Records

Solving a Stackelberg Game on Transportation Networks in a Dynamic Crime Scenario: A Mixed Approach on Multi-Layer Networks

Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology

PyVision: Agentic Vision with Dynamic Tooling

Single-pass Adaptive Image Tokenization for Minimum Program Search

Multigranular Evaluation for Brain Visual Decoding

Multi-Granular Spatio-Temporal Token Merging for Training-Free Acceleration of Video LLMs

EXPO: Stable Reinforcement Learning with Expressive Policies

Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling

Why is Your Language Model a Poor Implicit Reward Model?

Reinforcement Learning with Action Chunking

Scaling RL to Long Videos

MIRIX: Multi-Agent Memory System for LLM-Based Agents

Low Resource Reconstruction Attacks Through Benign Prompts

Probing Experts' Perspectives on AI-Assisted Public Speaking Training

Towards Continuous Home Cage Monitoring: An Evaluation of Tracking and Identification Strategies for Laboratory Mice

DTECT: Dynamic Topic Explorer & Context Tracker

Agentic Retrieval of Topics and Insights from Earnings Calls

BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems

Created by

Haebom

저자

Andy K. Zhang, Joey Ji, Celeste Menders, Riya Dulepet, Thomas Qin, Ron Y. Wang, Junrong Wu, Kyleen Liao, Jiliang Li, Jinghan Hu, Sara Hong, Nardos Demilew, Shivatmica Murgai, Jason Tran, Nishka Kacheria, Ethan Ho, Denis Liu, Lauren McLane, Olivia Bruvik, Dai-Rong Han, Seungwoo Kim, Akhil Vyas, Cuiyuanxiu Chen, Ryan Li, Weiran Xu, Jonathan Z. Ye, Prerit Choudhary, Siddharth M. Bhatia, Vikram Sivashankar, Yuxuan Bao, Dawn Song, Dan Boneh, Daniel E. Ho, Percy Liang

개요

본 논문은 진화하는 실제 시스템에서 공격 및 방어 사이버 역량을 포착하는 최초의 프레임워크를 제시한다. BountyBench라는 인스턴스를 통해 복잡한 실제 코드베이스를 가진 25개의 시스템을 설정하고, 취약성 라이프사이클을 포착하기 위해 Detect(새로운 취약성 탐지), Exploit(특정 취약성 악용), Patch(특정 취약성 패치) 세 가지 작업 유형을 정의했다. Detect 작업을 위해 새로운 성공 지표를 구성하고, 40개의 버그 바운티(10달러~30,485달러)를 추가하여 작업 난이도를 조절하는 새로운 전략을 고안했다. Claude Code, OpenAI Codex CLI, GPT-4.1, Gemini 2.5 Pro Preview, Claude 3.7 Sonnet Thinking, DeepSeek-R1 등 8개의 에이전트를 평가한 결과, OpenAI Codex CLI: o3-high, Custom Agent with Claude 3.7 Sonnet Thinking, OpenAI Codex CLI: o4-mini가 상위 성능을 보였다. 특히 OpenAI Codex CLI 기반 에이전트는 방어(Patch) 능력이 뛰어났다.

시사점, 한계점

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시사점:

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실제 시스템에서 AI 에이전트의 공격 및 방어 사이버 역량을 평가하는 새로운 프레임워크와 벤치마크(BountyBench) 제시.

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다양한 AI 에이전트의 공격 및 방어 성능 비교 분석을 통해 각 에이전트의 강점과 약점 파악.

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취약성 탐지, 악용, 패치 작업에 대한 새로운 성공 지표 및 작업 난이도 조절 전략 제시.

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AI 기반 사이버 보안 시스템 개발 및 향상에 대한 중요한 시사점 제공.

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한계점:

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평가에 사용된 시스템 수(25개)와 버그 바운티 수(40개)가 상대적으로 제한적일 수 있음.

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실제 세계의 모든 사이버 공격 시나리오를 완벽하게 반영하지 못할 수 있음.

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평가에 사용된 AI 에이전트의 종류가 제한적일 수 있으며, 다른 에이전트를 포함한 추가적인 연구가 필요함.

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수동 환경 설정 과정의 노력과 시간 소모. 더 자동화된 환경 설정 방법이 필요할 수 있음.

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