Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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VideoPDE: Unified Generative PDE Solving via Video Inpainting Diffusion Models

Prefix-Tuning+: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention

Graph-Convolutional-Beta-VAE for Synthetic Abdominal Aorta Aneurysm Generation

A Production Scheduling Framework for Reinforcement Learning Under Real-World Constraints

ROSAQ: Rotation-based Saliency-Aware Weight Quantization for Efficiently Compressing Large Language Models

Seewo's Submission to MLC-SLM: Lessons learned from Speech Reasoning Language Models

SeqPE: Transformer with Sequential Position Encoding

No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns

IKDiffuser: Fast and Diverse Inverse Kinematics Solution Generation for Multi-arm Robotic Systems

Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems

Adaptive Composition of Machine Learning as a Service (MLaaS) for IoT Environments

Discrete Audio Tokens: More Than a Survey!

FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation

Inherently Faithful Attention Maps for Vision Transformers

Reparameterized LLM Training via Orthogonal Equivalence Transformation

MultiMatch: Multihead Consistency Regularization Matching for Semi-Supervised Text Classification

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms

CellCLIP -- Learning Perturbation Effects in Cell Painting via Text-Guided Contrastive Learning

EuroLLM-9B: Technical Report

Incentivizing Reasoning for Advanced Instruction-Following of Large Language Models

EEG2TEXT-CN: An Exploratory Study of Open-Vocabulary Chinese Text-EEG Alignment via Large Language Model and Contrastive Learning on ChineseEEG

MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning

CSVQA: A Chinese Multimodal Benchmark for Evaluating STEM Reasoning Capabilities of VLMs

KGMark: A Diffusion Watermark for Knowledge Graphs

Representing local protein environments with atomistic foundation models

Accelerating RLHF Training with Reward Variance Increase

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

PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation

REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning

MSVIT: Improving Spiking Vision Transformer Using Multi-scale Attention Fusion

Abacus: A Cost-Based Optimizer for Semantic Operator Systems

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems

CAPTURE: Context-Aware Prompt Injection Testing and Robustness Enhancement

Chatting with Papers: A Hybrid Approach Using LLMs and Knowledge Graphs

Patho-R1: A Multimodal Reinforcement Learning-Based Pathology Expert Reasoner

LongCodeBench: Evaluating Coding LLMs at 1M Context Windows

H$^3$DP: Triply-Hierarchical Diffusion Policy for Visuomotor Learning

Convert Language Model into a Value-based Strategic Planner

Graph RAG for Legal Norms: A Hierarchical, Temporal and Deterministic Approach

CAPO: Cost-Aware Prompt Optimization

Spatiotemporal Learning of Brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention for Cognitive and Psychiatric Applications

The Backfiring Effect of Weak AI Safety Regulation

Assessing Consistency and Reproducibility in the Outputs of Large Language Models: Evidence Across Diverse Finance and Accounting Tasks

Achieving Unbiased Multi-Instance Learning via Balanced Fine-Grained Positive-Unlabeled Learning

Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression

SOPBench: Evaluating Language Agents at Following Standard Operating Procedures and Constraints

Effect of Selection Format on LLM Performance

Reward Shaping to Mitigate Reward Hacking in RLHF

SAE-V: Interpreting Multimodal Models for Enhanced Alignment

LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification

Target Speaker Extraction through Comparing Noisy Positive and Negative Audio Enrollments

Hardware-Friendly Static Quantization Method for Video Diffusion Transformers

PredictaBoard: Benchmarking LLM Score Predictability

Towards Geo-Culturally Grounded LLM Generations

Diverse Topology Optimization using Modulated Neural Fields

Counterfactual-Consistency Prompting for Relative Temporal Understanding in Large Language Models

NAROCE: A Neural Algorithmic Reasoner Framework for Online Complex Event Detection

Bridging Voting and Deliberation with Algorithms: Field Insights from vTaiwan and Kultur Komitee

From tools to thieves: Measuring and understanding public perceptions of AI through crowdsourced metaphors

The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs

Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models

Agent Laboratory: Using LLM Agents as Research Assistants

LLMs Help Alleviate the Cross-Subject Variability in Brain Signal and Language Alignment

Uncertainty-Aware Critic Augmentation for Hierarchical Multi-Agent EV Charging Control

Parallel Greedy Best-First Search with a Bound on Expansions Relative to Sequential Search

PunchBench: Benchmarking MLLMs in Multimodal Punchline Comprehension

BESSTIE: A Benchmark for Sentiment and Sarcasm Classification for Varieties of English

LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior

Geometric Signatures of Compositionality Across a Language Model's Lifetime

AssistantX: An LLM-Powered Proactive Assistant in Collaborative Human-Populated Environment

MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping

What is the Right Notion of Distance between Predict-then-Optimize Tasks?

QuantFactor REINFORCE: Mining Steady Formulaic Alpha Factors with Variance-bounded REINFORCE

MALSIGHT: Exploring Malicious Source Code and Benign Pseudocode for Iterative Binary Malware Summarization

Bridging Social Media and Search Engines: Dredge Words and the Detection of Unreliable Domains

Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG

Quality-aware Masked Diffusion Transformer for Enhanced Music Generation

InkSight: Offline-to-Online Handwriting Conversion by Teaching Vision-Language Models to Read and Write

Exploring news intent and its application: A theory-driven approach

Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures

AgentOrchestra: A Hierarchical Multi-Agent Framework for General-Purpose Task Solving

ConsistencyChecker: Tree-based Evaluation of LLM Generalization Capabilities

A Conjecture on a Fundamental Trade-Off between Certainty and Scope in Symbolic and Generative AI

Comment on The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

TIP-Search: Time-Predictable Inference Scheduling for Market Prediction under Uncertain Load

AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning

Large Language Models' Reasoning Stalls: An Investigation into the Capabilities of Frontier Models

OrgAccess: A Benchmark for Role Based Access Control in Organization Scale LLMs

SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning

Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis

Arbitrarily Applicable Same/Opposite Relational Responding with NARS

ShorterBetter: Guiding Reasoning Models to Find Optimal Inference Length for Efficient Reasoning

Behaviour Discovery and Attribution for Explainable Reinforcement Learning

Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible

Chain-of-Thought Reasoning In The Wild Is Not Always Faithful

Activation Space Interventions Can Be Transferred Between Large Language Models

Planning of Heuristics: Strategic Planning on Large Language Models with Monte Carlo Tree Search for Automating Heuristic Optimization

MAGELLAN: Metacognitive predictions of learning progress guide autotelic LLM agents in large goal spaces

Adaptive Composition of Machine Learning as a Service (MLaaS) for IoT Environments

Created by

Haebom

저자

Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah, Aneesh Krishna, Monowar Bhuyan

개요

본 논문은 사물 인터넷(IoT) 환경의 역동적인 특성으로 인해 머신러닝 서비스(MLaaS) 구성의 장기적인 효율성이 저해되는 문제를 해결하기 위해 적응형 MLaaS 구성 프레임워크를 제안한다. IoT 환경의 불확실성과 변동성으로 인해 데이터 분포의 변동(예: 개념 이동 및 데이터 이질성), 시스템 요구 사항의 변화(예: 확장성 요구 및 리소스 제약) 등이 발생한다. 제안된 프레임워크는 저성능 MLaaS 서비스를 식별하는 서비스 평가 모델과 최적의 대체 서비스를 필터링하는 후보 선택 모델을 통합한다. 또한, 상황별 다중 무장 밴딧 최적화 전략을 사용하여 MLaaS 구성을 점진적으로 업데이트하는 적응형 구성 메커니즘을 개발하여 진화하는 IoT 제약 조건에 지속적으로 적응하면서 서비스 품질(QoS)을 유지하고 처음부터 다시 구성하는 데 필요한 계산 비용을 줄인다. 실제 데이터 세트에 대한 실험 결과는 제안된 접근 방식의 효율성을 보여준다.

시사점, 한계점

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시사점:

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IoT 환경의 역동적인 특성에 적응하는 효율적인 MLaaS 구성 프레임워크 제시

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서비스 평가 및 후보 선택 모델을 통한 최적의 MLaaS 서비스 선택 가능

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상황별 다중 무장 밴딧 최적화 전략을 활용한 점진적 구성 업데이트로 QoS 유지 및 계산 비용 절감

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실제 데이터셋을 이용한 실험을 통해 접근 방식의 효율성 검증

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한계점:

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실험 데이터셋의 범용성 및 일반화 가능성에 대한 추가 검증 필요

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다양한 유형의 IoT 환경 및 MLaaS 서비스에 대한 적용 가능성 및 성능 평가 필요

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프레임워크의 복잡성 및 구현의 어려움에 대한 논의 필요

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장기간 운영 시 발생 가능한 문제점 및 해결 방안에 대한 추가 연구 필요

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