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.

Computational Blueprints: Generating Isomorphic Mathematics Problems with Large Language Models

Lightweight Diffusion-based Framework for Online Imagined Speech Decoding in Aphasia

Neurophysiological Characteristics of Adaptive Reasoning for Creative Problem-Solving Strategy

DANS-KGC: Diffusion Based Adaptive Negative Sampling for Knowledge Graph Completion

Data Descriptions from Large Language Models with Influence Estimation

SparseRM: A Lightweight Preference Modeling with Sparse Autoencoder

Toward Robust EEG-based Intention Decoding during Misarticulated Speech in Aphasia

Confidence-Aware Neural Decoding of Overt Speech from EEG: Toward Robust Brain-Computer Interfaces

WaterMod: Modular Token-Rank Partitioning for Probability-Balanced LLM Watermarking

GAMA: A Neural Neighborhood Search Method with Graph-aware Multi-modal Attention for Vehicle Routing Problem

Alignment-Aware Quantization for LLM Safety

Operational machine learning for remote spectroscopic detection of CH$_{4}$ point sources

Towards AI-Assisted Generation of Military Training Scenarios

ResearchRubrics: A Benchmark of Prompts and Rubrics For Evaluating Deep Research Agents

AIA Forecaster: Technical Report

Making LLMs Reliable When It Matters Most: A Five-Layer Architecture for High-Stakes Decisions

AI-Driven Contribution Evaluation and Conflict Resolution: A Framework & Design for Group Workload Investigation

Beyond Fact Retrieval: Episodic Memory for RAG with Generative Semantic Workspaces

Think Before You Retrieve: Learning Test-Time Adaptive Search with Small Language Models

Procedural Knowledge Improves Agentic LLM Workflows

Beyond Correctness: Confidence-Aware Reward Modeling for Enhancing Large Language Model Reasoning

Agentic Educational Content Generation for African Languages on Edge Devices

Analysing Environmental Efficiency in AI for X-Ray Diagnosis

SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models

Perceptually Aligning Representations of Music via Noise-Augmented Autoencoders

Rethinking Metrics and Diffusion Architecture for 3D Point Cloud Generation

DeepEyesV2: Toward Agentic Multimodal Model

MERaLiON-SER: Robust Speech Emotion Recognition Model for English and SEA Languages

Minimal and Mechanistic Conditions for Behavioral Self-Awareness in LLMs

multiMentalRoBERTa: A Fine-tuned Multiclass Classifier for Mental Health Disorder

Addressing divergent representations from causal interventions on neural networks

Alternative Fairness and Accuracy Optimization in Criminal Justice

Leveraging LLM-based agents for social science research: insights from citation network simulations

Conversational Collective Intelligence (CCI) using Hyperchat AI in a Real-world Forecasting Task

Explaining Human Choice Probabilities with Simple Vector Representations

Development of the Bioinspired Tendon-Driven DexHand 021 with Proprioceptive Compliance Control

GraphCliff: Short-Long Range Gating for Subtle Differences but Critical Changes

AutoAdv: Automated Adversarial Prompting for Multi-Turn Jailbreaking of Large Language Models

MM-UNet: Morph Mamba U-shaped Convolutional Networks for Retinal Vessel Segmentation

RobustFSM: Submodular Maximization in Federated Setting with Malicious Clients

Tool Zero: Training Tool-Augmented LLMs via Pure RL from Scratch

Reg-DPO: SFT-Regularized Direct Preference Optimization with GT-Pair for Improving Video Generation

Reasoning Planning for Language Models

Aligning Brain Signals with Multimodal Speech and Vision Embeddings

Calibrating and Rotating: A Unified Framework for Weight Conditioning in PEFT

FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models

Beyond Data Scarcity Optimizing R3GAN for Medical Image Generation from Small Datasets

Inside CORE-KG: Evaluating Structured Prompting and Coreference Resolution for Knowledge Graphs

Learning from N-Tuple Data with M Positive Instances: Unbiased Risk Estimation and Theoretical Guarantees

Universal Spectral Tokenization via Self-Supervised Panchromatic Representation Learning

DynaSpec: Context-aware Dynamic Speculative Sampling for Large-Vocabulary Language Models

Meronymic Ontology Extraction via Large Language Models

Robust Driving Control for Autonomous Vehicles: An Intelligent General-sum Constrained Adversarial Reinforcement Learning Approach

DPCformer: An Interpretable Deep Learning Model for Genomic Prediction in Crops

The Markovian Thinker

scUnified: An AI-Ready Standardized Resource for Single-Cell RNA Sequencing Analysis

Data-Centric Elastic Pipeline Parallelism for Efficient Long-Context LLM Training

Security-aware Semantic-driven ISAC via Paired Adversarial Residual Networks

TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decoding

Pure Vision Language Action (VLA) Models: A Comprehensive Survey

UniPixel: Unified Object Referring and Segmentation for Pixel-Level Visual Reasoning

Assisting the Grading of a Handwritten General Chemistry Exam with Artificial Intelligence

Privacy-Preserving Personalization in Education: A Federated Recommender System for Student Performance Prediction

UNO: Unifying One-stage Video Scene Graph Generation via Object-Centric Visual Representation Learning

Normality and the Turing Test

GUARD: Guideline Upholding Test through Adaptive Role-play and Jailbreak Diagnostics for LLMs

Cross-Platform E-Commerce Product Categorization and Recategorization: A Multimodal Hierarchical Classification Approach

ANO : Faster is Better in Noisy Landscape

Generative Medical Event Models Improve with Scale

ComoRAG: A Cognitive-Inspired Memory-Organized RAG for Stateful Long Narrative Reasoning

LLMCARE: early detection of cognitive impairment via transformer models enhanced by LLM-generated synthetic data

Oblivionis: A Lightweight Learning and Unlearning Framework for Federated Large Language Models

Rethinking Tokenization for Rich Morphology: The Dominance of Unigram over BPE and Morphological Alignment

Discovering Spatial Correlations of Earth Observations for weather forecasting by using Graph Structure Learning

Forecasting When to Forecast: Accelerating Diffusion Models with Confidence-Gated Taylor

Universal Neurons in GPT-2: Emergence, Persistence, and Functional Impact

Embedding-Aware Quantum-Classical SVMs for Scalable Quantum Machine Learning

RaGS: Unleashing 3D Gaussian Splatting from 4D Radar and Monocular Cues for 3D Object Detection

Controllable Hybrid Captioner for Improved Long-form Video Understanding

Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning

When Person Re-Identification Meets Event Camera: A Benchmark Dataset and An Attribute-guided Re-Identification Framework

Evaluating LLM-based Workflows for Switched-Mode Power Supply Design

Monitoring Risks in Test-Time Adaptation

White-Basilisk: A Hybrid Model for Code Vulnerability Detection

Bridging the Plausibility-Validity Gap by Fine-Tuning a Reasoning-Enhanced LLM for Chemical Synthesis and Discovery

CoRe: Benchmarking LLMs Code Reasoning Capabilities through Static Analysis Tasks

DP-Fusion: Token-Level Differentially Private Inference for Large Language Models

Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks

GPT, But Backwards: Exactly Inverting Language Model Outputs

Visual Structures Helps Visual Reasoning: Addressing the Binding Problem in VLMs

ReCode: Updating Code API Knowledge with Reinforcement Learning

Time-Prompt: Integrated Heterogeneous Prompts for Unlocking LLMs in Time Series Forecasting

Sekai: A Video Dataset towards World Exploration

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Towards Competent AI for Fundamental Analysis in Finance: A Benchmark Dataset and Evaluation

A Fairness-Aware Strategy for B5G Physical-layer Security Leveraging Reconfigurable Intelligent Surfaces

Bridging Weakly-Supervised Learning and VLM Distillation: Noisy Partial Label Learning for Efficient Downstream Adaptation

Data Leakage and Deceptive Performance: A Critical Examination of Credit Card Fraud Detection Methodologies

GRAM: Spatial general-purpose audio representation models for real-world applications

Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications

EngramNCA: a Neural Cellular Automaton Model of Memory Transfer

Created by

Haebom

저자

Etienne Guichard, Felix Reimers, Mia Kvalsund, Mikkel Lepper{\o}d, Stefano Nichele

개요

EngramNCA는 세포 내부 메모리 채널을 통합한 신경 세포 자동장치(NCA)로, 시냅스 변형을 넘어 세포 내 기전까지 포함하는 기억 저장에 대한 최근 생물학적 증거에서 영감을 받았습니다. GeneCA(불변의 "유전자" 암호를 포함하는 시드 세포로부터 구별되는 형태를 개발하도록 훈련된 NCA)와 GenePropCA(가시적인 상태를 변경하지 않고 세포의 개인 "유전적" 메모리를 조절하는 보조 NCA)라는 두 가지 구성 요소로 구성됩니다. 이 아키텍처를 통해 가시 채널과 개인 채널의 상호 작용을 통해 복잡한 형태의 인코딩 및 전파가 가능해지며, 공유된 "유전적" 기질로부터 다양한 구조의 성장을 촉진합니다. EngramNCA는 계층적이고 공존하는 형태의 출현을 지원하며, 인공 시스템에서 분산된 메모리 저장 및 전송에 대한 통찰력을 제공합니다.

시사점, 한계점

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시사점:

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적응적이고 자기 조직화 시스템 개발에 대한 잠재적 함의 제시.

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생물학적 및 인공적 맥락 모두에서 메모리 메커니즘에 대한 광범위한 이해에 기여.

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분산된 메모리 저장 및 전송에 대한 새로운 통찰력 제공.

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계층적이고 공존하는 형태의 출현을 지원하는 새로운 아키텍처 제시.

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한계점:

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현재까지는 모델의 한계점이나 제약에 대한 구체적인 언급이 논문에 포함되어 있지 않음.

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생물학적 메모리 시스템과의 직접적인 비교 및 검증 연구가 부족할 수 있음.

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모델의 확장성 및 실제 응용 가능성에 대한 추가적인 연구 필요.

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