Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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Self-Questioning Language Models

Beyond risk: A proto-framework for assessing the societal impact of AI systems

Supervised Dynamic Dimension Reduction with Deep Neural Network

EmoSteer-TTS: Fine-Grained and Training-Free Emotion-Controllable Text-to-Speech via Activation Steering

LLMs Have a Heart of Stone: Demystifying the Soft Thinking Ability of Large Reasoning Models

Industrial LLM-based Code Optimization under Regulation: A Mixture-of-Agents Approach

Reliable Evaluation Protocol for Low-Precision Retrieval

Landsat30-AU: A Vision-Language Dataset for Australian Landsat Imagery

Tool-integrated Reinforcement Learning for Repo Deep Search

CauKer: classification time series foundation models can be pretrained on synthetic data only

Context-Adaptive Multi-Prompt Embedding with Large Language Models for Vision-Language Alignment

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

HyCodePolicy: Hybrid Language Controllers for Multimodal Monitoring and Decision in Embodied Agents

Entity Representation Learning Through Onsite-Offsite Graph for Pinterest Ads

Evaluating User Experience in Conversational Recommender Systems: A Systematic Review Across Classical and LLM-Powered Approaches

Spatial-Frequency Aware for Object Detection in RAW Image

Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations

NCCR: to Evaluate the Robustness of Neural Networks and Adversarial Examples

ChartM$^3$: Benchmarking Chart Editing with Multimodal Instructions

From Entanglement to Alignment: Representation Space Decomposition for Unsupervised Time Series Domain Adaptation

EcoTransformer: Attention without Multiplication

Bob's Confetti: Phonetic Memorization Attacks in Music and Video Generation

SDBench: A Comprehensive Benchmark Suite for Speaker Diarization

True Multimodal In-Context Learning Needs Attention to the Visual Context

Gauge Flow Models

Zero-Shot Neural Architecture Search with Weighted Response Correlation

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

CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations

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

A Comparative Study of Specialized LLMs as Dense Retrievers

Sign Spotting Disambiguation using Large Language Models

UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields

Thought Anchors: Which LLM Reasoning Steps Matter?

UITron-Speech: Towards Automated GUI Agents Based on Speech Instructions

15,500 Seconds: Lean UAV Classification Using EfficientNet and Lightweight Fine-Tuning

AtmosMJ: Revisiting Gating Mechanism for AI Weather Forecasting Beyond the Year Scale

On the Fundamental Impossibility of Hallucination Control in Large Language Models

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR

Text-Only Reasoning Unleashes Zero-Shot Multimodal Evaluators

CAIN: Hijacking LLM-Humans Conversations via Malicious System Prompts

Explain Less, Understand More: Jargon Detection via Personalized Parameter-Efficient Fine-tuning

What Lives? A meta-analysis of diverse opinions on the definition of life

A Generative Neural Annealer for Black-Box Combinatorial Optimization

GRILL: Gradient Signal Restoration in Ill-Conditioned Layers to Enhance Adversarial Attacks on Autoencoders

CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering

Mj\"olnir: A Deep Learning Parametrization Framework for Global Lightning Flash Density

RGB-Event based Pedestrian Attribute Recognition: A Benchmark Dataset and An Asymmetric RWKV Fusion Framework

ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive Learning

Beyond Wide-Angle Images: Structure-to-Detail Video Portrait Correction via Unsupervised Spatiotemporal Adaptation

CITRAS: Covariate-Informed Transformer for Time Series Forecasting

Rubric Is All You Need: Enhancing LLM-based Code Evaluation With Question-Specific Rubrics

Empirical Analysis of Sim-and-Real Cotraining of Diffusion Policies for Planar Pushing from Pixels

SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language Models

The Impact of Item-Writing Flaws on Difficulty and Discrimination in Item Response Theory

Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM Decoding

Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Pull-Based Query Scheduling for Goal-Oriented Semantic Communication

Accelerating Focal Search in Multi-Agent Path Finding with Tighter Lower Bounds

RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks

UltraSTF: Ultra-Compact Model for Large-Scale Spatio-Temporal Forecasting

PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models

Foundation Model of Electronic Medical Records for Adaptive Risk Estimation

Tool Unlearning for Tool-Augmented LLMs

Vision without Images: End-to-End Computer Vision from Single Compressive Measurements

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias

3DTTNet: Multimodal Fusion-Based 3D Traversable Terrain Modeling for Off-Road Environments

DOGR: Towards Versatile Visual Document Grounding and Referring

Real-World Offline Reinforcement Learning from Vision Language Model Feedback

Causality-Driven Audits of Model Robustness

AUTALIC: A Dataset for Anti-AUTistic Ableist Language In Context

Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projection

pyhgf: A neural network library for predictive coding

Human Bias in the Face of AI: Examining Human Judgment Against Text Labeled as AI Generated

AVG-LLaVA: An Efficient Large Multimodal Model with Adaptive Visual Granularity

Parse Trees Guided LLM Prompt Compression

One Model, Any Conjunctive Query: Graph Neural Networks for Answering Queries over Incomplete Knowledge Graphs

A Value Based Parallel Update MCTS Method for Multi-Agent Cooperative Decision Making of Connected and Automated Vehicles

Fairness Definitions in Language Models Explained

CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control

Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting

Long-Term Visual Object Tracking with Event Cameras: An Associative Memory Augmented Tracker and A Benchmark Dataset

Hulk: A Universal Knowledge Translator for Human-Centric Tasks

From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited

Environmental Sound Classification on An Embedded Hardware Platform

Data Dependency Inference for Industrial Code Generation Based on UML Sequence Diagrams

InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation

SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning with LLM-Based Agents

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization

Higher Gauge Flow Models

Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models

IS-Bench: Evaluating Interactive Safety of VLM-Driven Embodied Agents in Daily Household Tasks

SLR: Automated Synthesis for Scalable Logical Reasoning

The SWE-Bench Illusion: When State-of-the-Art LLMs Remember Instead of Reason

APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning

Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets

Learning to Inference Adaptively for Multimodal Large Language Models

Efficient rule induction by ignoring pointless rules

Why the Agent Made that Decision: Contrastive Explanation Learning for Reinforcement Learning

Evaluating Detection Thresholds: The Impact of False Positives and Negatives on Super-Resolution Ultrasound Localization Microscopy

Dynaword: From One-shot to Continuously Developed Datasets

Created by

Haebom

저자

Kenneth Enevoldsen, Kristian N{\o}rgaard Jensen, Jan Kostkan, Balazs Szabo, Marton Kardos, Kirten Vad, Johan Heinsen, Andrea Blasi Nunez, Gianluca Barmina, Jacob Nielsen, Rasmus Larsen, Peter Vahlstrup, Per M{\o}ldrup Dalum, Desmond Elliott, Lukas Galke, Peter Schneider-Kamp, Kristoffer Nielbo

개요

본 논문은 자연어 처리 분야에서 대규모 데이터셋 개발 및 활용의 세 가지 주요 과제, 즉 1) 모호한 라이선스로 인한 사용, 공유 및 파생 저작물 제한, 2) 지속적인 커뮤니티 기여와 장기적인 유지 관리를 저해하는 정적 데이터셋 배포, 3) 출판팀에 국한된 품질 보증 프로세스를 해결하기 위해 Dynaword 접근법과 Danish Dynaword를 제시한다. Dynaword는 커뮤니티 협업을 통해 지속적으로 업데이트될 수 있는 대규모 개방형 데이터셋을 생성하기 위한 프레임워크이며, Danish Dynaword는 이 접근법의 타당성을 검증하고 잠재력을 보여주는 구체적인 구현이다. Danish Dynaword는 기존 데이터셋보다 네 배 이상 많은 토큰을 포함하고 있으며, 전적으로 개방형 라이선스를 사용하며, 산업계와 연구계의 다양한 기여를 받았다. 또한 데이터 형식, 품질 및 문서화를 보장하기 위한 경량 테스트를 포함하여 지속적인 커뮤니티 기여 및 데이터셋 발전을 위한 지속 가능한 프레임워크를 구축한다.

시사점, 한계점

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시사점:

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커뮤니티 기여 기반의 지속적으로 업데이트되는 대규모 개방형 데이터셋 생성 프레임워크 제시

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Danish Dynaword를 통해 Dynaword 접근법의 실현 가능성 및 효용성 검증

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기존 데이터셋 대비 훨씬 큰 규모(네 배 이상의 토큰)의 개방형 데이터셋 제공

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데이터 품질 및 지속 가능성을 위한 경량 테스트 및 문서화 시스템 구축

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한계점:

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Dynaword 접근법의 확장성 및 다양한 언어/도메인으로의 적용 가능성에 대한 추가적인 연구 필요

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커뮤니티 기여를 위한 효과적인 관리 및 참여 유도 메커니즘에 대한 추가적인 고찰 필요

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Danish Dynaword의 특징이 다른 언어 및 도메인의 데이터셋 구축에도 적용 가능한지에 대한 검증 필요

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