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Merge Kernel for Bayesian Optimization on Permutation Space

Demographic-aware fine-grained classification of pediatric wrist fractures

Generative Multi-Target Cross-Domain Recommendation

ParaStudent: Generating and Evaluating Realistic Student Code by Teaching LLMs to Struggle

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models

EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos

Inversion-DPO: Precise and Efficient Post-Training for Diffusion Models

A Simple Baseline for Stable and Plastic Neural Networks

WildFX: A DAW-Powered Pipeline for In-the-Wild Audio FX Graph Modeling

From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation

Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

How Not to Detect Prompt Injections with an LLM

Critiques of World Models

The role of large language models in UI/UX design: A systematic literature review

LearnLens: LLM-Enabled Personalized, Curriculum-Grounded Feedback with Educators in the Loop

STACK: Adversarial Attacks on LLM Safeguard Pipelines

ZonUI-3B: A Lightweight Vision-Language Model for Cross-Resolution GUI Grounding

Understanding Reasoning in Thinking Language Models via Steering Vectors

Agentic Neural Networks: Self-Evolving Multi-Agent Systems via Textual Backpropagation

EvolveNav: Self-Improving Embodied Reasoning for LLM-Based Vision-Language Navigation

TextDiffuser-RL: Efficient and Robust Text Layout Optimization for High-Fidelity Text-to-Image Synthesis

SpecMaskFoley: Steering Pretrained Spectral Masked Generative Transformer Toward Synchronized Video-to-audio Synthesis via ControlNet

Exploring Graph Representations of Logical Forms for Language Modeling

DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs

CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors

Hands-On: Segmenting Individual Signs from Continuous Sequences

Can we ease the Injectivity Bottleneck on Lorentzian Manifolds for Graph Neural Networks?

Align Your Rhythm: Generating Highly Aligned Dance Poses with Gating-Enhanced Rhythm-Aware Feature Representation

HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results

An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model

Evaluating link prediction: New perspectives and recommendations

Learning to Reason at the Frontier of Learnability

Stonefish: Supporting Machine Learning Research in Marine Robotics

Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning

On the Transfer of Knowledge in Quantum Algorithms

Code Readability in the Age of Large Language Models: An Industrial Case Study from Atlassian

Bias in Decision-Making for AI's Ethical Dilemmas: A Comparative Study of ChatGPT and Claude

ASTRID -- An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems

Consistency of Responses and Continuations Generated by Large Language Models on Social Media

From Code to Compliance: Assessing ChatGPT's Utility in Designing an Accessible Webpage -- A Case Study

Temporal reasoning for timeline summary in social media

Invisible Textual Backdoor Attacks based on Dual-Trigger

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models

Two-Stage Pretraining for Molecular Property Prediction in the Wild

Towards Practical Operation of Deep Reinforcement Learning Agents in Real-World Network Management at Open RAN Edges

An Approach for Auto Generation of Labeling Functions for Software Engineering Chatbots

Bridging Local and Global Knowledge via Transformer in Board Games

Entropy Loss: An Interpretability Amplifier of 3D Object Detection Network for Intelligent Driving

FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image Translation

On Pre-training of Multimodal Language Models Customized for Chart Understanding

Visual Grounding Methods for Efficient Interaction with Desktop Graphical User Interfaces

Instruct-MusicGen: Unlocking Text-to-Music Editing for Music Language Models via Instruction Tuning

Meta4XNLI: A Crosslingual Parallel Corpus for Metaphor Detection and Interpretation

SecurePose: Automated Face Blurring and Human Movement Kinematics Extraction from Videos Recorded in Clinical Settings

Improved DDIM Sampling with Moment Matching Gaussian Mixtures

Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges

From Roots to Rewards: Dynamic Tree Reasoning with RL

Illuminating the Three Dogmas of Reinforcement Learning under Evolutionary Light

Instance space analysis of the capacitated vehicle routing problem

Multi-Agent LLMs as Ethics Advocates for AI-Based Systems

GATSim: Urban Mobility Simulation with Generative Agents

Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?

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

Strategic Reflectivism In Intelligent Systems

SafeAgent: Safeguarding LLM Agents via an Automated Risk Simulator

What the F*ck Is Artificial General Intelligence?

Towards Reasoning Era: A Survey of Long Chain-of-Thoughts for Reasoning Large Language Models

From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios

To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization

BLAST: A Stealthy Backdoor Leverage Attack against Cooperative Multi-Agent Deep Reinforcement Learning based Systems

UniEmoX: Cross-modal Semantic-Guided Large-Scale Pretraining for Universal Scene Emotion Perception

CorMulT: A Semi-supervised Modality Correlation-aware Multimodal Transformer for Sentiment Analysis

Toward Temporal Causal Representation Learning with Tensor Decomposition

Kolmogorov Arnold Networks (KANs) for Imbalanced Data -- An Empirical Perspective

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining

Lessons from the TREC Plain Language Adaptation of Biomedical Abstracts (PLABA) track

Multi-Centre Validation of a Deep Learning Model for Scoliosis Assessment

The Emotion-Memory Link: Do Memorability Annotations Matter for Intelligent Systems?

DENSE: Longitudinal Progress Note Generation with Temporal Modeling of Heterogeneous Clinical Notes Across Hospital Visits

Edge Intelligence with Spiking Neural Networks

VLA-Mark: A cross modal watermark for large vision-language alignment model

Noradrenergic-inspired gain modulation attenuates the stability gap in joint training

A multi-strategy improved snake optimizer for three-dimensional UAV path planning and engineering problems

Photonic Fabric Platform for AI Accelerators

OrthoInsight: Rib Fracture Diagnosis and Report Generation Based on Multi-Modal Large Models

CSD-VAR: Content-Style Decomposition in Visual Autoregressive Models

A segmented robot grasping perception neural network for edge AI

Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need

DUALRec: A Hybrid Sequential and Language Model Framework for Context-Aware Movie Recommendation

Exploiting Primacy Effect To Improve Large Language Models

Generalist Forecasting with Frozen Video Models via Latent Diffusion

Convergent transformations of visual representation in brains and models

Preprint: Did I Just Browse A Website Written by LLMs?

The Levers of Political Persuasion with Conversational AI

Political Leaning and Politicalness Classification of Texts

Self-supervised learning on gene expression data

Using LLMs to identify features of personal and professional skills in an open-response situational judgment test

BreastSegNet: Multi-label Segmentation of Breast MRI

Created by

Haebom

Author

Qihang Li, Jichen Yang, Yaqian Chen, Yuwen Chen, Hanxue Gu, Lars J. Grimm, Maciej A. Mazurowski

Outline

In this paper, we present BreastSegNet, a multi-label segmentation algorithm for quantitative analysis of breast MRI images. Unlike previous breast MRI segmentation methods that focus on only a few anatomical structures (e.g., fibrous tissue or tumors), BreastSegNet includes nine anatomical structures: fibrous tissue, blood vessels, muscles, bones, lesions, lymph nodes, heart, liver, and implants. The researchers manually annotated 1,123 MRI slices after review and revision by an expert radiologist. After benchmarking nine segmentation models, including U-Net, SwinUNet, UNet++, SAM, MedSAM, and nnU-Net with multiple ResNet-based encoders, nnU-Net ResEncM achieved the highest performance, achieving an average Dice score of 0.694 for all labels. In particular, it achieved Dice scores exceeding 0.73 for heart, liver, muscle, fibrous tissue, and bone, and approached 0.90 for heart and liver. All model code and weights are publicly available, and data will be made public in the future.

Takeaways, Limitations

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Takeaways:

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We present BreastSegNet, a comprehensive multi-label segmentation algorithm for quantitative analysis of breast MRI.

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Contributes to breast cancer diagnosis and treatment planning by enabling accurate segmentation of nine anatomical structures.

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We verified the excellent performance of the nnU-Net ResEncM model and made the related code and weights public to ensure the reproducibility and expandability of the research.

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Future disclosure of data is expected to facilitate further research and development.

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Limitations:

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The current dataset consists of 1123 MRI slices, so further studies using larger datasets are needed.

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Because the dataset has not yet been made public, verification and use by other researchers are limited.

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Performance for certain labels (e.g., lesions, lymph nodes) may be relatively lower than for other labels.

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