Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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Enhancing Password Security Through a High-Accuracy Scoring Framework Using Random Forests

Potent but Stealthy: Rethink Profile Pollution against Sequential Recommendation via Bi-level Constrained Reinforcement Paradigm

Leveraging Large Language Models for Use Case Model Generation from Software Requirements

Enhancing PIBT via Multi-Action Operations

PressTrack-HMR: Pressure-Based Top-Down Multi-Person Global Human Mesh Recovery

Thinking Forward and Backward: Multi-Objective Reinforcement Learning for Retrieval-Augmented Reasoning

PAN: A World Model for General, Interactable, and Long-Horizon World Simulation

Learning the Basis: A Kolmogorov-Arnold Network Approach Embedding Green's Function Priors

Automatic Grid Updates for Kolmogorov-Arnold Networks using Layer Histograms

Remodeling Semantic Relationships in Vision-Language Fine-Tuning

Biologically-Informed Hybrid Membership Inference Attacks on Generative Genomic Models

MVU-Eval: Towards Multi-Video Understanding Evaluation for Multimodal LLMs

Explainable Cross-Disease Reasoning for Cardiovascular Risk Assessment from LDCT

Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations

Personalized Chain-of-Thought Summarization of Financial News for Investor Decision Support

Search Is Not Retrieval: Decoupling Semantic Matching from Contextual Assembly in RAG

Does AI-Assisted Coding Deliver? A Difference-in-Differences Study of Cursor's Impact on Software Projects

CORE - A Cell-Level Coarse-to-Fine Image Registration Engine for Multi-stain Image Alignment

Text to Robotic Assembly of Multi Component Objects using 3D Generative AI and Vision Language Models

WOD-E2E: Waymo Open Dataset for End-to-End Driving in Challenging Long-tail Scenarios

Xiaoice: Training-Free Video Understanding via Self-Supervised Spatio-Temporal Clustering of Semantic Features

A Critical Review of the Need for Knowledge-Centric Evaluation of Quranic Recitation

The Markovian Thinker: Architecture-Agnostic Linear Scaling of Reasoning

Artificial-Intelligence Grading Assistance for Handwritten Components of a Calculus Exam

Computing Wasserstein Barycenters through Gradient Flows

Enhancing the development of Cherenkov Telescope Array control software with Large Language Models

GPT and Prejudice: A Sparse Approach to Understanding Learned Representations in Large Language Models

One-Shot Multi-Label Causal Discovery in High-Dimensional Event Sequences

FHIR-AgentBench: Benchmarking LLM Agents for Realistic Interoperable EHR Question Answering

Towards Practical Multi-label Causal Discovery in High-Dimensional Event Sequences via One-Shot Graph Aggregation

Inference Offloading for Cost-Sensitive Binary Classification at the Edge

Collapse of Irrelevant Representations (CIR) Ensures Robust and Non-Disruptive LLM Unlearning

Zero-Shot Referring Expression Comprehension via Vison-Language True/False Verification

Retrieval-Augmented Generation for Reliable Interpretation of Radio Regulations

Dual-Mode Deep Anomaly Detection for Medical Manufacturing: Structural Similarity and Feature Distance

ManipDreamer3D : Synthesizing Plausible Robotic Manipulation Video with Occupancy-aware 3D Trajectory

ChronoGraph: A Real-World Graph-Based Multivariate Time Series Dataset

Bine Trees: Enhancing Collective Operations by Optimizing Communication Locality

EcomMMMU: Strategic Utilization of Visuals for Robust Multimodal E-commerce Models

Improving Pre-Trained Vision-Language-Action Policies with Model-Based Search

Beyond Frequency: Seeing Subtle Cues Through the Lens of Spatial Decomposition for Fine-Grained Visual Classification

Test-Time Reinforcement Learning for GUI Grounding via Region Consistency

Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction

Application-Specific Component-Aware Structured Pruning of Deep Neural Networks in Control via Soft Coefficient Optimization

Cameras as Relative Positional Encoding

The Prompt War: How AI Decides on a Military Intervention

xLSTMAD: A Powerful xLSTM-based Method for Anomaly Detection

Why Do Open-Source LLMs Struggle with Data Analysis? A Systematic Empirical Study

Interpretable and Granular Video-Based Quantification of Motor Characteristics from the Finger Tapping Test in Parkinson Disease

Feedback-MPPI: Fast Sampling-Based MPC via Rollout Differentiation -- Adios low-level controllers

VFEFL: Privacy-Preserving Federated Learning against Malicious Clients via Verifiable Functional Encryption

Understanding Human-AI Trust in Education

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Scaling Textual Gradients via Sampling-Based Momentum

Caption This, Reason That: VLMs Caught in the Middle

BroadGen: A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations

Revisiting Residual Connections: Orthogonal Updates for Stable and Efficient Deep Networks

Scalable Quantum State Preparation via Large-Language-Model-Driven Discovery

OODTE: A Differential Testing Engine for the ONNX Optimizer

Constructing an Optimal Behavior Basis for the Option Keyboard

Bridging LMS and generative AI: dynamic course content integration (DCCI) for enhancing student satisfaction and engagement via the ask ME assistant

ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation

Feature-EndoGaussian: Feature Distilled Gaussian Splatting in Surgical Deformable Scene Reconstruction

Abn-BLIP: Abnormality-aligned Bootstrapping Language-Image Pre-training for Pulmonary Embolism Diagnosis and Report Generation from CTPA

FactReasoner: A Probabilistic Approach to Long-Form Factuality Assessment for Large Language Models

MMTEB: Massive Multilingual Text Embedding Benchmark

Enhanced Structured Lasso Pruning with Class-wise Information

CoAT: Chain-of-Associated-Thoughts Framework for Enhancing Large Language Models Reasoning

Graph of Attacks with Pruning: Optimizing Stealthy Jailbreak Prompt Generation for Enhanced LLM Content Moderation

Siren: A Learning-Based Multi-Turn Attack Framework for Simulating Real-World Human Jailbreak Behaviors

Enhanced Suicidal Ideation Detection from Social Media Using a CNN-BiLSTM Hybrid Model

Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations

Reducing the Scope of Language Models

Matryoshka Pilot: Learning to Drive Black-Box LLMs with LLMs

Captions Speak Louder than Images: Generalizing Foundation Models for E-commerce from High-quality Multimodal Instruction Data

Multi-Turn Interactions for Text-to-SQL with Large Language Models

Differentiating between human-written and AI-generated texts using linguistic features automatically extracted from an online computational tool

Spikingformer: A Key Foundation Model for Spiking Neural Networks

SOM Directions are Better than One: Multi-Directional Refusal Suppression in Language Models

An Efficient Training Pipeline for Reasoning Graphical User Interface Agents

National Institute on Aging PREPARE Challenge: Early Detection of Cognitive Impairment Using Speech -- The SpeechCARE Solution

Information Capacity: Evaluating the Efficiency of Large Language Models via Text Compression

Enhancing Logical Expressiveness in Graph Neural Networks via Path-Neighbor Aggregation

WaterMod: Modular Token-Rank Partitioning for Probability-Balanced LLM Watermarking

Green AI: A systematic review and meta-analysis of its definitions, lifecycle models, hardware and measurement attempts

GHOST: Solving the Traveling Salesman Problem on Graphs of Convex Sets

A Brain Cell Type Resource Created by Large Language Models and a Multi-Agent AI System for Collaborative Community Annotation

LiveResearchBench: A Live Benchmark for User-Centric Deep Research in the Wild

Ax-Prover: A Deep Reasoning Agentic Framework for Theorem Proving in Mathematics and Quantum Physics

PsychCounsel-Bench: Evaluating the Psychology Intelligence of Large Language Models

DOoM: Difficult Olympiads of Math

From Capabilities to Performance: Evaluating Key Functional Properties of LLM Architectures in Penetration Testing

Planning Agents on an Ego-Trip: Leveraging Hybrid Ego-Graph Ensembles for Improved Tool Retrieval in Enterprise Task Planning

PITA: Preference-Guided Inference-Time Alignment for LLM Post-Training

Small Models Struggle to Learn from Strong Reasoners

Unlocking Efficient Vehicle Dynamics Modeling via Analytic World Models

Enhancing Conflict Resolution in Language Models via Abstract Argumentation

Discussion Graph Semantics of First-Order Logic with Equality for Reasoning about Discussion and Argumentation

A Comprehensive Survey on Multi-modal Conversational Emotion Recognition with Deep Learning

Black-Box On-Policy Distillation of Large Language Models

Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?

Created by

Haebom

저자

Kai Yan, Yufei Xu, Zhengyin Du, Xuesong Yao, Zheyu Wang, Xiaowen Guo, Jiecao Chen

개요

본 논문은 최근 LLM 벤치마크의 난이도가 초등학교 수준에서 첨단 문제까지 급격히 상승함에 따라 인간의 지능을 능가하는 시점에 임박했다는 연구자들의 낙관적 전망에 의문을 제기합니다. LLM의 놀라운 추론 능력이 진정한 지능에서 비롯되는지, 아니면 단순히 인터넷 수준의 훈련 데이터에서 목격한 해결책을 반복하는 것인지 연구하기 위해, 조건을 미묘하게 변경하여 간단한 추론 문제에 대한 LLM의 암기 행동을 감지하는 새로운 다중 모드 벤치마크인 RoR-Bench를 제안하고 실증 분석을 수행합니다. 실험 결과, 최첨단 LLM들이 극심한 암기 행동을 보이는 것을 발견했습니다. 조건에서 한 문구만 변경해도 OpenAI-o1 및 DeepSeek-R1과 같은 최고 모델의 초등학교 수준 산술 및 추론 문제 해결 능력이 60%나 저하되었습니다. 이러한 결과는 최첨단 LLM의 진정한 지능 수준을 재평가해야 함을 시사하는 경종입니다.

시사점, 한계점

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시사점: 최첨단 LLM의 추론 능력에 대한 과도한 낙관론에 대한 경고를 제시합니다. LLM이 단순히 암기 기반으로 문제를 해결할 수 있다는 것을 보여주는 실험 결과는 LLM의 지능 수준에 대한 재평가의 필요성을 강조합니다. RoR-Bench는 LLM의 암기 행동을 탐지하고 진정한 추론 능력을 평가하는 데 유용한 벤치마크로 활용될 수 있습니다.

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한계점: RoR-Bench가 특정 유형의 문제와 미묘한 조건 변경에만 집중되어 있어 LLM의 전반적인 추론 능력을 완전히 평가하는 데 한계가 있을 수 있습니다. 다양한 유형의 문제와 더 광범위한 조건 변화에 대한 추가 연구가 필요합니다. 또한, 벤치마크의 설계 및 평가 과정에 대한 자세한 설명이 부족하여 재현성과 일반화 가능성에 대한 검증이 필요합니다.

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