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.

Merge-of-Thought Distillation

OTESGN: Optimal Transport-Enhanced Syntactic-Semantic Graph Networks for Aspect-Based Sentiment Analysis

MESH -- Understanding Videos Like Human: Measuring Hallucinations in Large Video Models

Adapting Vision-Language Models for Neutrino Event Classification in High-Energy Physics

Symmetry-Guided Multi-Agent Inverse Reinforcement Learning

AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

Expert-Guided Explainable Few-Shot Learning for Medical Image Diagnosis

Towards Generalized Routing: Model and Agent Orchestration for Adaptive and Efficient Inference

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining

Demo: Healthcare Agent Orchestrator (HAO) for Patient Summarization in Molecular Tumor Boards

Focusing by Contrastive Attention: Enhancing VLMs' Visual Reasoning

Beyond the Pre-Service Horizon: Infusing In-Service Behavior for Improved Financial Risk Forecasting

On Synthesis of Timed Regular Expressions

TinyDef-DETR: A DETR-based Framework for Defect Detection in Transmission Lines from UAV Imagery

LiDAR-BIND-T: Improved and Temporally Consistent Sensor Modality Translation and Fusion for Robotic Applications

From Vision to Validation: A Theory- and Data-Driven Construction of a GCC-Specific AI Adoption Index

A Comprehensive Guide to Differential Privacy: From Theory to User Expectations

The Architecture of AI Transformation: Four Strategic Patterns and an Emerging Frontier

FLM-Audio: Natural Monologues Improves Native Full-Duplex Chatbots via Dual Training

Deep Learning-Based Rock Particulate Classification Using Attention-Enhanced ConvNeXt

The Information Dynamics of Generative Diffusion

Data-Augmented Few-Shot Neural Stencil Emulation for System Identification of Computer Models

Group Expectation Policy Optimization for Heterogeneous Reinforcement Learning

Pretrained Conformers for Audio Fingerprinting and Retrieval

Towards Scalable Training for Handwritten Mathematical Expression Recognition

To Theoretically Understand Transformer-Based In-Context Learning for Optimizing CSMA

Klear-CodeTest: Scalable Test Case Generation for Code Reinforcement Learning

HiD-VAE: Interpretable Generative Recommendation via Hierarchical and Disentangled Semantic IDs

MagicGUI: A Foundational Mobile GUI Agent with Scalable Data Pipeline and Reinforcement Fine-tuning

villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models

New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants

Can Large Language Models Understand As Well As Apply Patent Regulations to Pass a Hands-On Patent Attorney Test?

Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound

Uncertainty Estimation by Human Perception versus Neural Models

Persistent Homology of Topic Networks for the Prediction of Reader Curiosity

Task Matters: Knowledge Requirements Shape LLM Responses to Context-Memory Conflict

Crack Path Prediction with Operator Learning using Discrete Particle System data Generation

Diffusion Graph Neural Networks for Robustness in Olfaction Sensors and Datasets

MM-Prompt: Cross-Modal Prompt Tuning for Continual Visual Question Answering

An Ontology-Driven Graph RAG for Legal Norms: A Structural, Temporal, and Deterministic Approach

Combating Falsification of Speech Videos with Live Optical Signatures (Extended Version)

Early Exit and Multi Stage Knowledge Distillation in VLMs for Video Summarization

Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Review

Parasite: A Steganography-based Backdoor Attack Framework for Diffusion Models

Towards Adaptive Memory-Based Optimization for Enhanced Retrieval-Augmented Generation

Entropy-Gated Branching for Efficient Test-Time Reasoning

SWI: Speaking with Intent in Large Language Models

Byzantine-Robust Federated Learning Using Generative Adversarial Networks

VeriSafe Agent: Safeguarding Mobile GUI Agent via Logic-based Action Verification

MIND: Towards Immersive Psychological Healing with Multi-agent Inner Dialogue

V-HOP: Visuo-Haptic 6D Object Pose Tracking

EgoAgent: A Joint Predictive Agent Model in Egocentric Worlds

Knowledge-Guided Biomarker Identification for Label-Free Single-Cell RNA-Seq Data: A Reinforcement Learning Perspective

MERaLiON-SpeechEncoder: Towards a Speech Foundation Model for Singapore and Beyond

RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution

IDEATOR: Jailbreaking and Benchmarking Large Vision-Language Models Using Themselves

DeepVoting: Learning and Fine-Tuning Voting Rules with Canonical Embeddings

Rethinking Disentanglement under Dependent Factors of Variation

Discovering physical laws with parallel symbolic enumeration

Semantic Augmentation in Images using Language

Algorithmic Collusion by Large Language Models

A minimal coalition logic

Deep Reinforcement Learning for Inventory Networks: Toward Reliable Policy Optimization

Inconsistency Handling in Prioritized Databases with Universal Constraints: Complexity Analysis and Links with Active Integrity Constraints

Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference

CogGuide: Human-Like Guidance for Zero-Shot Omni-Modal Reasoning

TreeGPT: Pure TreeFFN Encoder-Decoder Architecture for Structured Reasoning Without Attention Mechanisms

Robix: A Unified Model for Robot Interaction, Reasoning and Planning

KROMA: Ontology Matching with Knowledge Retrieval and Large Language Models

Scaling LLM Planning: NL2FLOW for Parametric Problem Generation and Rigorous Evaluation

Optimizing Length Compression in Large Reasoning Models

LLMs for sensory-motor control: Combining in-context and iterative learning

Effort-aware Fairness: Incorporating a Philosophy-informed, Human-centered Notion of Effort into Algorithmic Fairness Metrics

Simulating Human-like Daily Activities with Desire-driven Autonomy

Enhancing Few-Shot Transfer Learning with Optimized Multi-Task Prompt Tuning through Modular Prompt Composition

ButterflyQuant: Ultra-low-bit LLM Quantization through Learnable Orthogonal Butterfly Transforms

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models

SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning

Feasibility-Guided Fair Adaptive Offline Reinforcement Learning for Medicaid Care Management

Retrieval-Augmented Generation for Reliable Interpretation of Radio Regulations

Explaining Concept Drift through the Evolution of Group Counterfactuals

LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering

Mechanistic Learning with Guided Diffusion Models to Predict Spatio-Temporal Brain Tumor Growth

Graph Alignment via Dual-Pass Spectral Encoding and Latent Space Communication

ObjectReact: Learning Object-Relative Control for Visual Navigation

Fluent but Unfeeling: The Emotional Blind Spots of Language Models

Invisible Attributes, Visible Biases: Exploring Demographic Shortcuts in MRI-based Alzheimer's Disease Classification

An improved educational competition optimizer with multi-covariance learning operators for global optimization problems

Improving Video Diffusion Transformer Training by Multi-Feature Fusion and Alignment from Self-Supervised Vision Encoders

A modified RIME algorithm with covariance learning and diversity enhancement for numerical optimization

Towards Explainable Job Title Matching: Leveraging Semantic Textual Relatedness and Knowledge Graphs

Explainable AI for Accelerated Microstructure Imaging: A SHAP-Guided Protocol on the Connectome 2.0 scanner

Incorporating AI Incident Reporting into Telecommunications Law and Policy: Insights from India

OpenFake: An Open Dataset and Platform Toward Large-Scale Deepfake Detection

Prompt Pirates Need a Map: Stealing Seeds helps Stealing Prompts

Resource-Efficient Glioma Segmentation on Sub-Saharan MRI

ENSI: Efficient Non-Interactive Secure Inference for Large Language Models

We're Still Doing It (All) Wrong: Recommender Systems, Fifteen Years Later

LLMs Don't Know Their Own Decision Boundaries: The Unreliability of Self-Generated Counterfactual Explanations

MetaLLMix : An XAI Aided LLM-Meta-learning Based Approach for Hyper-parameters Optimization

Towards Scalable Training for Handwritten Mathematical Expression Recognition

Created by

Haebom

저자

Haoyang Li, Jiaqing Li, Jialun Cao, Zongyuan Yang, Yongping Xiong

개요

본 논문은 수기 수학 식 인식(HMER) 분야의 데이터 부족 문제를 해결하기 위해, 대규모 LaTeX 렌더링 수식과 제한된 수기 수식을 통합하는 새로운 방법을 제안합니다. 대규모 LaTeX 수식 생성을 위한 확장 가능한 데이터 엔진을 개발하여 8천만 개 이상의 고품질 학습 인스턴스로 구성된, 현재까지 가장 큰 수식 데이터셋인 Tex80M을 구축했습니다. 이를 기반으로, Tex80M과 상대적으로 작은 HME 데이터셋을 혼합 학습하여 최초의 대규모 HMER 모델인 TexTeller를 제안합니다. TexTeller는 거의 모든 벤치마크에서 최첨단(SOTA) 성능을 달성했습니다. 모델, 데이터셋, 코드베이스를 공개하여 후속 연구를 지원합니다.

시사점, 한계점

•

시사점:

◦

대규모 수식 데이터셋 Tex80M 구축을 통해 HMER 분야의 데이터 부족 문제 해결에 기여.

◦

대규모 HMER 모델 TexTeller 개발을 통해 SOTA 성능 달성.

◦

모델, 데이터셋, 코드베이스의 공개를 통한 HMER 분야 연구 활성화.

•

한계점:

◦

LaTeX 기반의 합성 데이터셋 사용으로 인한 수기 데이터와의 도메인 격차 존재 가능성.

◦

Tex80M의 데이터 품질에 대한 추가적인 검증 필요.

◦

실제 수기 수식의 다양성을 완벽하게 반영하지 못할 가능성.

Made with Slashpage