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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.

SeC: Advancing Complex Video Object Segmentation via Progressive Concept Construction

GUI-G$^2$: Gaussian Reward Modeling for GUI Grounding

Romance, Relief, and Regret: Teen Narratives of Chatbot Overreliance

Supernova: Achieving More with Less in Transformer Architectures

GR-3 Technical Report

EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Contro

AI-Enhanced Precision in Sport Taekwondo: Increasing Fairness, Speed, and Trust in Competition (FST.ai)

Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models

NeuroHD-RA: Neural-distilled Hyperdimensional Model with Rhythm Alignment

IPPRO: Importance-based Pruning with PRojective Offset for Magnitude-indifferent Structural Pruning

Lessons from the TREC Plain Language Adaptation of Biomedical Abstracts (PLABA) track

Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters

Physical models realizing the transformer architecture of large language models

GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities

Multimodal Coordinated Online Behavior: Trade-offs and Strategies

A Survey of Deep Learning for Geometry Problem Solving

Prompt4Trust: A Reinforcement Learning Prompt Augmentation Framework for Clinically-Aligned Confidence Calibration in Multimodal Large Language Models

Pre-Training LLMs on a budget: A comparison of three optimizers

OPC: One-Point-Contraction Unlearning Toward Deep Feature Forgetting

Adaptive Gaussian Mixture Models-based Anomaly Detection for under-constrained Cable-Driven Parallel Robots

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

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

Omni-Router: Sharing Routing Decisions in Sparse Mixture-of-Experts for Speech Recognition

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling

The Joys of Categorical Conformal Prediction

Towards Accurate and Efficient 3D Object Detection for Autonomous Driving: A Mixture of Experts Computing System on Edge

Capacity Planning and Scheduling for Jobs with Uncertainty in Resource Usage and Duration

FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization

Neural Approaches for Multi-Objective Routing on Multigraphs

Diffusion-Based Electrocardiography Noise Quantification via Anomaly Detection

CogStream: Context-guided Streaming Video Question Answering

Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems

Towards provable probabilistic safety for scalable embodied AI systems

SenWiCh: Sense-Annotation of Low-Resource Languages for WiC using Hybrid Methods

Human Empathy as Encoder: AI-Assisted Depression Assessment in Special Education

Multimodal Forecasting of Sparse Intraoperative Hypotension Events Powered by Language Model

Autocomp: LLM-Driven Code Optimization for Tensor Accelerators

ViP$^2$-CLIP: Visual-Perception Prompting with Unified Alignment for Zero-Shot Anomaly Detection

ReMi: A Random Recurrent Neural Network Approach to Music Production

Aitomia: Your Intelligent Assistant for AI-Driven Atomistic and Quantum Chemical Simulations

A Goal-Oriented Reinforcement Learning-Based Path Planning Algorithm for Modular Self-Reconfigurable Satellites

A Method for the Architecture of a Medical Vertical Large Language Model Based on Deepseek R1

Balancing Robustness and Efficiency in Embedded DNNs Through Activation Function Selection

Antithetic Sampling for Top-k Shapley Identification

GeoFlow-SLAM: A Robust Tightly-Coupled RGBD-Inertial and Legged Odometry Fusion SLAM for Dynamic Legged Robotics

SciFi-Benchmark: Leveraging Science Fiction To Improve Robot Behavior

ETCH: Generalizing Body Fitting to Clothed Humans via Equivariant Tightness

Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $\mu$P Parametrization

Curating Demonstrations using Online Experience

OMNISEC: LLM-Driven Provenance-based Intrusion Detection via Retrieval-Augmented Behavior Prompting

PRISM: High-Resolution & Precise Counterfactual Medical Image Generation using Language-guided Stable Diffusion

Reasoning Does Not Necessarily Improve Role-Playing Ability

BioMaze: Benchmarking and Enhancing Large Language Models for Biological Pathway Reasoning

Revealing Bias Formation in Deep Neural Networks Through the Geometric Mechanisms of Human Visual Decoupling

Conformal Predictions for Human Action Recognition with Vision-Language Models

Cross-Encoder Rediscovers a Semantic Variant of BM25

DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection

RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment

R-Bot: An LLM-based Query Rewrite System

Towards a Universal 3D Medical Multi-modality Generalization via Learning Personalized Invariant Representation

Atomic Calibration of LLMs in Long-Form Generations

LibEER: A Comprehensive Benchmark and Algorithm Library for EEG-based Emotion Recognition

Aligning AI with Public Values: Deliberation and Decision-Making for Governing Multimodal LLMs in Political Video Analysis

VitaGlyph: Vitalizing Artistic Typography with Flexible Dual-branch Diffusion Models

From homeostasis to resource sharing: Biologically and economically aligned multi-objective multi-agent AI safety benchmarks

V-RoAst: Visual Road Assessment. Can VLM be a Road Safety Assessor Using the iRAP Standard?

FLAIN: Mitigating Backdoor Attacks in Federated Learning via Flipping Weight Updates of Low-Activation Input Neurons

FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image Translation

Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge

Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers

LangBiTe: A Platform for Testing Bias in Large Language Models

Practical Insights into Knowledge Distillation for Pre-Trained Models

Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy

Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven Control

Gemini 2.5 Pro Capable of Winning Gold at IMO 2025

Hierarchical Budget Policy Optimization for Adaptive Reasoning

BioGraphFusion: Graph Knowledge Embedding for Biological Completion and Reasoning

Routine: A Structural Planning Framework for LLM Agent System in Enterprise

CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Assessing Adaptive World Models in Machines with Novel Games

A Multi-granularity Concept Sparse Activation and Hierarchical Knowledge Graph Fusion Framework for Rare Disease Diagnosis

An Integrated Framework of Prompt Engineering and Multidimensional Knowledge Graphs for Legal Dispute Analysis

Hierarchical Reasoning Model

The Unified Cognitive Consciousness Theory for Language Models: Anchoring Semantics, Thresholds of Activation, and Emergent Reasoning

DCG-SQL: Enhancing In-Context Learning for Text-to-SQL with Deep Contextual Schema Link Graph

InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification

R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory

Efficient Strategy Learning by Decoupling Searching and Pathfinding for Object Navigation

Alto: Orchestrating Distributed Compound AI Systems with Nested Ancestry

Toward A Causal Framework for Modeling Perception

ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning

MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning

Rethinking LLM-Based RTL Code Optimization Via Timing Logic Metamorphosis

Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty

Decoding Translation-Related Functional Sequences in 5'UTRs Using Interpretable Deep Learning Models

Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning

Never Come Up Empty: Adaptive HyDE Retrieval for Improving LLM Developer Support

AI-enhanced conversational agents for personalized asthma support Factors for engagement, value and efficacy

RAVine: Reality-Aligned Evaluation for Agentic Search

Experience is the Best Teacher: Grounding VLMs for Robotics through Self-Generated Memory

Assessing Adaptive World Models in Machines with Novel Games

Created by

Haebom

저자

Lance Ying, Katherine M. Collins, Prafull Sharma, Cedric Colas, Kaiya Ivy Zhao, Adrian Weller, Zenna Tavares, Phillip Isola, Samuel J. Gershman, Jacob D. Andreas, Thomas L. Griffiths, Francois Chollet, Kelsey R. Allen, Joshua B. Tenenbaum

개요

본 논문은 인간의 놀라운 적응력과 문제 해결 능력이 효율적인 내적 환경 표상(세계 모델) 구축 및 개선에 기반한다는 주장을 제기한다. 인공지능(AI) 분야에서 세계 모델에 대한 기존 연구는 대규모 데이터 학습을 통한 정적인 표상에 초점을 맞춘 반면, 본 논문은 상호작용과 탐색을 통한 새로운 환경에서의 효율적인 세계 모델 학습(세계 모델 유도)에 주목한다. 인지과학 연구를 바탕으로 세계 모델 유도에 대한 관점을 제시하고, AI에서 적응적 세계 모델을 평가하기 위한 새로운 평가 프레임워크를 제안한다. 구체적으로, 게임 구조가 지속적으로 새롭게 변하는 독창적인 게임 모음(novel games)을 기반으로 한 벤치마킹 패러다임을 제시하며, 게임 설계 기준 및 에이전트의 빠른 세계 모델 유도 능력을 평가하는 지표를 제안한다. 이를 통해 인간 수준의 빠른 적응력과 견고한 일반화 능력을 갖춘 AI 시스템 개발에 기여하고자 한다.

시사점, 한계점

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시사점:

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인간의 적응력을 AI에 적용하기 위한 새로운 관점 제시 (세계 모델 유도)

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AI 세계 모델 평가를 위한 새로운 벤치마킹 패러다임(novel games) 제안

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적응적 세계 모델의 효율성 및 효과성 평가를 위한 새로운 지표 제시

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인간 수준의 적응력과 일반화 능력을 갖춘 AGI 개발에 기여할 가능성 제시

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한계점:

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제안된 novel games의 구체적인 설계 및 구현에 대한 자세한 설명 부족

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제안된 평가 지표의 실효성 및 타당성에 대한 추가적인 검증 필요

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인간의 세계 모델 유도 과정에 대한 완벽한 이해 부족으로 인한 모델의 한계 존재 가능성

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제안된 프레임워크가 모든 유형의 세계 모델에 적용 가능한지에 대한 추가 연구 필요

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