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OPTIC-ER: A Reinforcement Learning Framework for Real-Time Emergency Response and Equitable Resource Allocation in Underserved African Communities
BioAnalyst: A Foundation Model for Biodiversity
Scaling Towards the Information Boundary of Instruction Sets: The Infinity Instruct Subject Technical Report
Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations
NeuroPhysNet: A FitzHugh-Nagumo-Based Physics-Informed Neural Network Framework for Electroencephalograph (EEG) Analysis and Motor Imagery Classification
PRO-V-R1: Reasoning Enhanced Programming Agent for RTL Verification
Large language models can learn and generalize steganographic chain-of-thought under process supervision
Turing Test 2.0: The General Intelligence Threshold
Consistency-based Abductive Reasoning over Perceptual Errors of Multiple Pre-trained Models in Novel Environments
Empowering Clients - Transformation of Design Processes Due to Generative AI
The Delusional Hedge Algorithm as a Model of Human Learning from Diverse Opinions
The Universal Weight Subspace Hypothesis
DraCo: Draft as CoT for Text-to-Image Preview and Rare Concept Generation
ShadowDraw: From Any Object to Shadow-Drawing Compositional Art
Semantic Soft Bootstrapping: Long Context Reasoning in LLMs without Reinforcement Learning
TV2TV: A Unified Framework for Interleaved Language and Video Generation
Structured Document Translation via Format Reinforcement Learning
SA-IQA: Redefining Image Quality Assessment for Spatial Aesthetics with Multi-Dimensional Rewards
David vs. Goliath: Can Small Models Win Big with Agentic AI in Hardware Design?
Multi-LLM Collaboration for Medication Recommendation
Meta-Learning for Quantum Optimization via Quantum Sequence Model
QKAN-LSTM: Quantum-inspired Kolmogorov-Arnold Long Short-term Memory
Arbitrage: Efficient Reasoning via Advantage-Aware Speculation
Model-Free Assessment of Simulator Fidelity via Quantile Curves
Reflection Removal through Efficient Adaptation of Diffusion Transformers
Evolutionary Architecture Search through Grammar-Based Sequence Alignment
Strategic Self-Improvement for Competitive Agents in AI Labour Markets
Balanced Few-Shot Episodic Learning for Accurate Retinal Disease Diagnosis
GeoPE:A Unified Geometric Positional Embedding for Structured Tensors
Realizable Abstractions: Near-Optimal Hierarchical Reinforcement Learning
LLMs Know More Than Words: A Genre Study with Syntax, Metaphor & Phonetics
CARL: Critical Action Focused Reinforcement Learning for Multi-Step Agent
Declarative Synthesis and Multi-Objective Optimization of Stripboard Circuit Layouts Using Answer Set Programming
ReflexFlow: Rethinking Learning Objective for Exposure Bias Alleviation in Flow Matching
Developing a General Personal Tutor for Education
SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs
Language Models as Semantic Teachers: Post-Training Alignment for Medical Audio Understanding
Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates
From Symptoms to Systems: An Expert-Guided Approach to Understanding Risks of Generative AI for Eating Disorders
SoK: a Comprehensive Causality Analysis Framework for Large Language Model Security
Setting up for failure: automatic discovery of the neural mechanisms of cognitive errors
287,872 Supermassive Black Holes Masses: Deep Learning Approaching Reverberation Mapping Accuracy
YingMusic-SVC: Real-World Robust Zero-Shot Singing Voice Conversion with Flow-GRPO and Singing-Specific Inductive Biases
YingMusic-Singer: Zero-shot Singing Voice Synthesis and Editing with Annotation-free Melody Guidance
Using Machine Learning to Take Stay-or-Go Decisions in Data-driven Drone Missions
Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges
UnwrapDiff: Conditional Diffusion for Robust InSAR Phase Unwrapping
SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs
Neural Policy Composition from Free Energy Minimization
OsmT: Bridging OpenStreetMap Queries and Natural Language with Open-source Tag-aware Language Models
E3AD: An Emotion-Aware Vision-Language-Action Model for Human-Centric End-to-End Autonomous Driving
Measuring the Unspoken: A Disentanglement Model and Benchmark for Psychological Analysis in the Wild
Towards an AI Fluid Scientist: LLM-Powered Scientific Discovery in Experimental Fluid Mechanics
Large Speech Model Enabled Semantic Communication
TimesNet-Gen: Deep Learning-based Site Specific Strong Motion Generation
Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap
Topology Matters: Measuring Memory Leakage in Multi-Agent LLMs
Semi Centralized Training Decentralized Execution Architecture for Multi Agent Deep Reinforcement Learning in Traffic Signal Control
SEASON: Mitigating Temporal Hallucination in Video Large Language Models via Self-Diagnostic Contrastive Decoding
When GenAI Meets Fake News: Understanding Image Cascade Dynamics on Reddit
When Robots Should Say "I Don't Know": Benchmarking Abstention in Embodied Question Answering
A Light-Weight Large Language Model File Format for Highly-Secure Model Distribution
Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function
RRPO: Robust Reward Policy Optimization for LLM-based Emotional TTS
Multi-Loss Learning for Speech Emotion Recognition with Energy-Adaptive Mixup and Frame-Level Attention
AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees
Detection of Intoxicated Individuals from Facial Video Sequences via a Recurrent Fusion Model
PhyVLLM: Physics-Guided Video Language Model with Motion-Appearance Disentanglement
Prototype-Based Semantic Consistency Alignment for Domain Adaptive Retrieval
UW-BioNLP at ChemoTimelines 2025: Thinking, Fine-Tuning, and Dictionary-Enhanced LLM Systems for Chemotherapy Timeline Extraction
GraphBench: Next-generation graph learning benchmarking
GuidNoise: Single-Pair Guided Diffusion for Generalized Noise Synthesis
Open-Ended Goal Inference through Actions and Language for Human-Robot Collaboration
NORi: An ML-Augmented Ocean Boundary Layer Parameterization
Automating Complex Document Workflows via Stepwise and Rollback-Enabled Operation Orchestration
Explainable Parkinsons Disease Gait Recognition Using Multimodal RGB-D Fusion and Large Language Models
Dual-Stream Spectral Decoupling Distillation for Remote Sensing Object Detection
Towards 6G Native-AI Edge Networks: A Semantic-Aware and Agentic Intelligence Paradigm
Adversarial Limits of Quantum Certification: When Eve Defeats Detection
FMA-Net++: Motion- and Exposure-Aware Real-World Joint Video Super-Resolution and Deblurring
MASE: Interpretable NLP Models via Model-Agnostic Saliency Estimation
STeP-Diff: Spatio-Temporal Physics-Informed Diffusion Models for Mobile Fine-Grained Pollution Forecasting
AutoGuard: A Self-Healing Proactive Security Layer for DevSecOps Pipelines Using Reinforcement Learning
Mitigating Object and Action Hallucinations in Multimodal LLMs via Self-Augmented Contrastive Alignment
Counting Without Running: Evaluating LLMs' Reasoning About Code Complexity
RGE-GCN: Recursive Gene Elimination with Graph Convolutional Networks for RNA-seq based Early Cancer Detection
DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle
Bayes-DIC Net: Estimating Digital Image Correlation Uncertainty with Bayesian Neural Networks
MANTRA: a Framework for Multi-stage Adaptive Noise TReAtment During Training
Evaluating Long-Context Reasoning in LLM-Based WebAgents
Gamma-from-Mono: Road-Relative, Metric, Self-Supervised Monocular Geometry for Vehicular Applications
Learning Single-Image Super-Resolution in the JPEG Compressed Domain
Bootstrapped Mixed Rewards for RL Post-Training: Injecting Canonical Action Order
Quantitative Analysis of Technical Debt and Pattern Violation in Large Language Model Architectures
The Initialization Determines Whether In-Context Learning Is Gradient Descent
Catching UX Flaws in Code: Leveraging LLMs to Identify Usability Flaws at the Development Stage
Hey GPT-OSS, Looks Like You Got It - Now Walk Me Through It! An Assessment of the Reasoning Language Models Chain of Thought Mechanism for Digital Forensics
Fine-Tuning ChemBERTa for Predicting Inhibitory Activity Against TDP1 Using Deep Learning
MVRoom: Controllable 3D Indoor Scene Generation with Multi-View Diffusion Models
CRAFT-E: A Neuro-Symbolic Framework for Embodied Affordance Grounding
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BrainCSD: A Hierarchical Consistency-Driven MoE Foundation Model for Unified Connectome Synthesis and Multitask Brain Trait Prediction
Created by
Haebom
Category
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저자
Xiongri Shen, Jiaqi Wang, Yi Zhong, Zhenxi Song, Leilei Zhao, Liling Li, Yichen Wei, Lingyan Liang, Shuqiang Wang, Baiying Lei, Demao Deng, Zhiguo Zhang
개요
BrainCSD는 기능적 연결성(FC)과 구조적 연결성(SC)을 함께 합성하고, 진단 및 예측과 같은 후속 디코딩 작업을 지원하는 계층적 혼합 전문가(MoE) 기반 모델이다. 뇌의 해부학적 구조를 기반으로 하는 세 가지 구성 요소(ROI별 MoE, 인코딩-활성화 MoE, 네트워크 인식 개선 MoE)를 특징으로 하며, FC 및 SC가 누락된 경우에도 우수한 성능을 보였다.
시사점, 한계점
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시사점:
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FC/SC 바이오마커의 효율적인 합성을 통해 임상적 활용성을 높임.
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누락된 모달리티 환경에서도 우수한 성능을 보임.
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다양한 다운스트림 작업(진단, 예측)에서 SOTA 달성.
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뇌 해부학적 구조를 반영한 모델 설계를 통해 해석 가능성 향상.
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한계점:
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모델의 복잡성으로 인한 훈련 및 배포의 어려움 가능성.
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특정 데이터셋에 대한 과적합 가능성.
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모델 성능의 일반화 가능성에 대한 추가 연구 필요.
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