Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers

Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning

MimicDreamer: Aligning Human and Robot Demonstrations for Scalable VLA Training

R-Capsule: Compressing High-Level Plans for Efficient Large Language Model Reasoning

DiTraj: training-free trajectory control for video diffusion transformer

Agribot: agriculture-specific question answer system

$\mathbf{Li_2}$: A Framework on Dynamics of Feature Emergence and Delayed Generalization

Dual-Head Reasoning Distillation: Improving Classifier Accuracy with Train-Time-Only Reasoning

Do Sparse Subnetworks Exhibit Cognitively Aligned Attention? Effects of Pruning on Saliency Map Fidelity, Sparsity, and Concept Coherence

Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy

Can Less Precise Be More Reliable? A Systematic Evaluation of Quantization's Impact on CLIP Beyond Accuracy

SiNGER: A Clearer Voice Distills Vision Transformers Further

i-LAVA: Insights on Low Latency Voice-2-Voice Architecture for Agents

Experience Deploying Containerized GenAI Services at an HPC Center

EmbeddingGemma: Powerful and Lightweight Text Representations

Beyond Sharp Minima: Robust LLM Unlearning via Feedback-Guided Multi-Point Optimization

Embedding Domain Knowledge for Large Language Models via Reinforcement Learning from Augmented Generation

Responsible AI Technical Report

Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks

Diversity Boosts AI-Generated Text Detection

SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer

APRIL: Active Partial Rollouts in Reinforcement Learning to Tame Long-tail Generation

Self-Evolving LLMs via Continual Instruction Tuning

Reinforced Generation of Combinatorial Structures: Applications to Complexity Theory

Joint Memory Frequency and Computing Frequency Scaling for Energy-efficient DNN Inference

StefaLand: An Efficient Geoscience Foundation Model That Improves Dynamic Land-Surface Predictions

Accurate and Efficient Low-Rank Model Merging in Core Space

Patterns in the Transition From Founder-Leadership to Community Governance of Open Source

Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search

Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning

WorldForge: Unlocking Emergent 3D/4D Generation in Video Diffusion Model via Training-Free Guidance

TreeIRL: Safe Urban Driving with Tree Search and Inverse Reinforcement Learning

Evaluating undergraduate mathematics examinations in the era of generative AI: a curriculum-level case study

Learning to Route: Per-Sample Adaptive Routing for Multimodal Multitask Prediction

MindVL: Towards Efficient and Effective Training of Multimodal Large Language Models on Ascend NPUs

FuseCodec: Semantic-Contextual Fusion and Supervision for Neural Codecs

TalkPlayData 2: An Agentic Synthetic Data Pipeline for Multimodal Conversational Music Recommendation

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

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving

DEPFusion: Dual-Domain Enhancement and Priority-Guided Mamba Fusion for UAV Multispectral Object Detection

COMPACT: Common-token Optimized Model Pruning Across Channels and Tokens

BranchGRPO: Stable and Efficient GRPO with Structured Branching in Diffusion Models

The Physical Basis of Prediction: World Model Formation in Neural Organoids via an LLM-Generated Curriculum

Diffusion Generative Models Meet Compressed Sensing, with Applications to Imaging and Finance

Co-Evolving Complexity: An Adversarial Framework for Automatic MARL Curricula

Grocery to General Merchandise: A Cross-Pollination Recommender using LLMs and Real-Time Cart Context

Do LLMs Adhere to Label Definitions? Examining Their Receptivity to External Label Definitions

GradES: Significantly Faster Training in Transformers with Gradient-Based Early Stopping

Can General-Purpose Omnimodels Compete with Specialists? A Case Study in Medical Image Segmentation

Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering

TReF-6: Inferring Task-Relevant Frames from a Single Demonstration for One-Shot Skill Generalization

Evaluating the Effectiveness of Transformer Layers in Wav2Vec 2.0, XLS-R, and Whisper for Speaker Identification Tasks

End-to-End On-Device Quantization-Aware Training for LLMs at Inference Cost

Automatic Question & Answer Generation Using Generative Large Language Model (LLM)

CORE-RAG: Lossless Compression for Retrieval-Augmented LLMs via Reinforcement Learning

What Matters in Data for DPO?

Type-Compliant Adaptation Cascades: Adapting Programmatic LM Workflows to Data

Speculative Safety-Aware Decoding

Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search

Coarse-to-Fine Personalized LLM Impressions for Streamlined Radiology Reports

ECHO: Frequency-aware Hierarchical Encoding for Variable-length Signals

Hard Examples Are All You Need: Maximizing GRPO Post-Training Under Annotation Budgets

Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration

Contrastive Representations for Temporal Reasoning

Semantic Discrepancy-aware Detector for Image Forgery Identification

G-CUT3R: Guided 3D Reconstruction with Camera and Depth Prior Integration

BLADE: Block-Sparse Attention Meets Step Distillation for Efficient Video Generation

PakBBQ: A Culturally Adapted Bias Benchmark for QA

MoQE: Improve Quantization Model performance via Mixture of Quantization Experts

Discerning minds or generic tutors? Evaluating instructional guidance capabilities in Socratic LLMs

Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts

AttriLens-Mol: Attribute Guided Reinforcement Learning for Molecular Property Prediction with Large Language Models

Sculptor: Empowering LLMs with Cognitive Agency via Active Context Management

CTTS: Collective Test-Time Scaling

The Geometry of Cortical Computation: Manifold Disentanglement and Predictive Dynamics in VCNet

Communicating Plans, Not Percepts: Scalable Multi-Agent Coordination with Embodied World Models

Can Language Models Discover Scaling Laws?

When Engineering Outruns Intelligence: Rethinking Instruction-Guided Navigation

A Markov Categorical Framework for Language Modeling

Moving Out: Physically-grounded Human-AI Collaboration

GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning

The Ever-Evolving Science Exam

Omni-Thinker: Scaling Multi-Task RL in LLMs with Hybrid Reward and Task Scheduling

GRID: Scalable Task-Agnostic Prompt-Based Continual Learning for Language Models

Learning to summarize user information for personalized reinforcement learning from human feedback

Making Language Model a Hierarchical Classifier

Vidar: Embodied Video Diffusion Model for Generalist Manipulation

BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search

Function Induction and Task Generalization: An Interpretability Study with Off-by-One Addition

Mitigating Watermark Forgery in Generative Models via Randomized Key Selection

Entropy-Memorization Law: Evaluating Memorization Difficulty of Data in LLMs

CoSteer: Collaborative Decoding-Time Personalization via Local Delta Steering

PRIME: Large Language Model Personalization with Cognitive Dual-Memory and Personalized Thought Process

Model Collapse Is Not a Bug but a Feature in Machine Unlearning for LLMs

Latent Chain-of-Thought? Decoding the Depth-Recurrent Transformer

Empirical Analysis Of Heuristic and Approximation Algorithms for the The Mutual-Visibility Problem

Learning to Segment for Vehicle Routing Problems

Theoretical Modeling of LLM Self-Improvement Training Dynamics Through Solver-Verifier Gap

Data Uniformity Improves Training Efficiency and More, with a Convergence Framework Beyond the NTK Regime

Semantic-guided Diverse Decoding for Large Language Model

Empirical Analysis Of Heuristic and Approximation Algorithms for the The Mutual-Visibility Problem

Created by

Haebom

저자

Vanja Stojanovic, Bor Panger\v{s}i\v{c}

개요

NP-완전 문제인 상호 가시성(MV) 문제에 대한 실증적 분석이 부족한 점을 해결하기 위해, 본 논문은 세 가지 알고리즘 (직접 무작위 휴리스틱, 하이퍼그래프 기반 근사, 유전자 알고리즘)을 구현하고, 다양한 합성 그래프 데이터셋 (분석적으로 알려진 $\mu(G)$ 값을 가진 데이터셋 포함)에서 평가했다.

시사점, 한계점

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소규모 그래프의 경우, 알고리즘이 이론적 경계에 부합하는 MV 집합 크기를 일관되게 달성했다.

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대규모 인스턴스의 경우, 해결책 크기가 이론적 한계에서 크게 벗어났다.

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엄격한 경계의 부재로 인해 절대적인 품질 평가가 어려웠다.

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알려진 최적 그래프에 대한 검증 결과, 유전자 알고리즘과 다른 휴리스틱이 가장 좋은 성능을 보였다.

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