[공지사항]을 빙자한 안부와 근황

Show more

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.

Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout

Energy Efficiency in AI for 5G and Beyond: A DeepRx Case Study

A PBN-RL-XAI Framework for Discovering a "Hit-and-Run" Therapeutic Strategy in Melanoma

(Almost) Free Modality Stitching of Foundation Models

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

SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems

Dually Hierarchical Drift Adaptation for Online Configuration Performance Learning

Tree-Structured Parzen Estimator Can Solve Black-Box Combinatorial Optimization More Efficiently

EXPO: Stable Reinforcement Learning with Expressive Policies

Reinforcement Learning with Action Chunking

On the Effect of Instruction Tuning Loss on Generalization

Hallucination Stations: On Some Basic Limitations of Transformer-Based Language Models

Text to model via SysML: Automated generation of dynamical system computational models from unstructured natural language text via enhanced System Modeling Language diagrams

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why

DRAGON: Dynamic RAG Benchmark On News

Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching

RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism

Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence

Stylometry recognizes human and LLM-generated texts in short samples

QLPro: Automated Code Vulnerability Discovery via LLM and Static Code Analysis Integration

Evaluating Multimodal Large Language Models on Educational Textbook Question Answering

FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model

MATE: LLM-Powered Multi-Agent Translation Environment for Accessibility Applications

DeInfoReg: A Decoupled Learning Framework for Better Training Throughput

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE

ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products

The Limits of Tractable Marginalization

A quantum semantic framework for natural language processing

ProtocolLLM: RTL Benchmark for SystemVerilog Generation of Communication Protocols

Deepfake Technology Unveiled: The Commoditization of AI and Its Impact on Digital Trust

Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning

Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback

Matrix Is All You Need

Temporal Chunking Enhances Recognition of Implicit Sequential Patterns

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems

PAN-Crafter: Learning Modality-Consistent Alignment for PAN-Sharpening

FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing

Traveling Across Languages: Benchmarking Cross-Lingual Consistency in Multimodal LLMs

FalseReject: A Resource for Improving Contextual Safety and Mitigating Over-Refusals in LLMs via Structured Reasoning

Multimodal Sentiment Analysis on CMU-MOSEI Dataset using Transformer-based Models

Nexus-Gen: Unified Image Understanding, Generation, and Editing via Prefilled Autoregression in Shared Embedding Space

Leveraging Large Language Models for Multi-Class and Multi-Label Detection of Drug Use and Overdose Symptoms on Social Media

Rethinking the Foundations for Continual Reinforcement Learning

Compositional Flows for 3D Molecule and Synthesis Pathway Co-design

Rethinking RoPE: A Mathematical Blueprint for N-dimensional Positional Embedding

Speculative Automated Refactoring of Imperative Deep Learning Programs to Graph Execution

Test-time Adaptation for Foundation Medical Segmentation Model without Parametric Updates

Style over Substance: Distilled Language Models Reason Via Stylistic Replication

AnnoPage Dataset: Dataset of Non-Textual Elements in Documents with Fine-Grained Categorization

Multi-View Node Pruning for Accurate Graph Representation

Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models

Voting or Consensus? Decision-Making in Multi-Agent Debate

Assistance or Disruption? Exploring and Evaluating the Design and Trade-offs of Proactive AI Programming Support

A Generative Approach to LLM Harmfulness Detection with Special Red Flag Tokens

Score-of-Mixture Training: Training One-Step Generative Models Made Simple via Score Estimation of Mixture Distributions

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Synthetic Datasets for Machine Learning on Spatio-Temporal Graphs using PDEs

Comply: Learning Sentences with Complex Weights inspired by Fruit Fly Olfaction

Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors

Few-Shot Radar Signal Recognition through Self-Supervised Learning and Radio Frequency Domain Adaptation

Transfer Learning Analysis of Variational Quantum Circuits

Plancraft: an evaluation dataset for planning with LLM agents

Fully Data-driven but Interpretable Human Behavioural Modelling with Differentiable Discrete Choice Model

A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation

Is Training Data Quality or Quantity More Impactful to Small Language Model Performance?

Searching Latent Program Spaces

The Pragmatic Frames of Spurious Correlations in Machine Learning: Interpreting How and Why They Matter

ComFairGNN: Community Fair Graph Neural Network

DroidSpeak: KV Cache Sharing for Cross-LLM Communication and Multi-LLM Serving

Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback

Large Language Models Engineer Too Many Simple Features For Tabular Data

Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control

IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback

SECURE: Semantics-aware Embodied Conversation under Unawareness for Lifelong Robot Learning

Advancing Depth Anything Model for Unsupervised Monocular Depth Estimation in Endoscopy

SA-GDA: Spectral Augmentation for Graph Domain Adaptation

The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances

State-Constrained Offline Reinforcement Learning

SimAD: A Simple Dissimilarity-based Approach for Time Series Anomaly Detection

Unified ODE Analysis of Smooth Q-Learning Algorithms

FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definition

Fine-grained Stateful Knowledge Exploration: Effective and Efficient Graph Retrieval with Large Language Models

Learning Safe Numeric Planning Action Models

Augmenting End-to-End Steering Angle Prediction with CAN Bus Data

EASTER: Embedding Aggregation-based Heterogeneous Models Training in Vertical Federated Learning

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks

Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures

VerifyBench: A Systematic Benchmark for Evaluating Reasoning Verifiers Across Domains

Is Human-Written Data Enough? The Challenge of Teaching Reasoning to LLMs Without RL or Distillation

Working with AI: Measuring the Occupational Implications of Generative AI

Establishing Best Practices for Building Rigorous Agentic Benchmarks

An Agentic Framework for Autonomous Metamaterial Modeling and Inverse Design

Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

BOOST: Bootstrapping Strategy-Driven Reasoning Programs for Program-Guided Fact-Checking

The Odyssey of the Fittest: Can Agents Survive and Still Be Good?

Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic Tools

ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning

AnnoPage Dataset: Dataset of Non-Textual Elements in Documents with Fine-Grained Categorization

Created by

Haebom

저자

Martin Ki\v{s}\v{s}, Michal Hradi\v{s}, Martina Dvo\v{r}akova, Vaclav Jirou\v{s}ek, Filip Kersch

개요

AnnoPage Dataset은 1485년부터 현재까지의 체코어와 독일어로 된 7,550페이지의 역사적 문서 페이지를 포함하는 새로운 데이터셋입니다. 19세기 후반과 20세기 초의 문서에 중점을 두고 있으며, 문서 레이아웃 분석과 객체 탐지 연구를 지원하도록 설계되었습니다. 각 페이지는 이미지, 지도, 장식 요소, 차트 등 25가지 비텍스트 요소 범주를 나타내는 축 정렬 경계 상자(AABB)로 주석이 달려 있으며, 체코 이미지 문서 처리 방법론을 따릅니다. 전문 사서가 정확성과 일관성을 보장하기 위해 주석을 작성했습니다. 여러 역사적 문서 데이터셋의 페이지를 통합하여 다양성을 높이고 연속성을 유지합니다. 데이터셋은 개발 및 테스트 하위 집합으로 나뉘며, 테스트 집합은 범주 분포를 유지하도록 신중하게 선택되었습니다. YOLO 및 DETR 객체 검출기를 사용한 기준 결과를 제공하여 향후 연구를 위한 참조 지점을 제시합니다. AnnoPage Dataset은 YOLO 형식의 정답 주석과 함께 Zenodo(https://doi.org/10.5281/zenodo.12788419)에서 공개적으로 사용할 수 있습니다.

시사점, 한계점

•

시사점:

◦

역사적 문서의 레이아웃 분석 및 객체 탐지 연구를 위한 새로운 대규모 데이터셋 제공.

◦

체코 이미지 문서 처리 방법론 기반의 정확하고 일관된 주석 제공.

◦

다양한 역사적 문서 페이지를 포함하여 일반화 성능 향상에 기여.

◦

YOLO 및 DETR 기반의 기준 성능 제공으로 향후 연구의 비교 기준 마련.

◦

공개적으로 접근 가능하여 연구 공동체에 기여.

•

한계점:

◦

주로 체코어와 독일어 문서에 집중되어 다른 언어의 문서에는 적용하기 어려울 수 있음.

◦

19세기 후반과 20세기 초의 문서에 편중되어 시대적 다양성이 부족할 수 있음.

◦

25가지 비텍스트 요소 범주만 포함되어 더욱 세분화된 분류가 필요할 수 있음.

◦

데이터셋의 크기가 다른 대규모 데이터셋에 비해 상대적으로 작을 수 있음.

Made with Slashpage