Search: “research”

ActiNet: An Open-Source Tool for Activity Intensity Classification of Wrist-Worn Accelerometry Using Self-Supervised Deep Learning

arXiv:2510.01712v2 Announce Type: replace Abstract: The use of accurate and reliable open-source human activity recognition (HAR) models on passively collected wrist-accelerometer data is essential in

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Research

Activation Function Design Sustains Plasticity in Continual Learning

DGX agent

arXiv:2509.22562v4 Announce Type: replace-cross Abstract: In independent, identically distributed (i.i.d.) training regimes, activation functions have been benchmarked extensively, and their differenc

researcharxiv-cs-ai

1 May 2026

AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning

arXiv:2604.27434v1 Announce Type: cross Abstract: Federated learning (FL) is a popular distributed learning paradigm in machine learning, which enables multiple clients to collaboratively train models

Adaptive Nonlinear MPC for Trajectory Tracking of An Overactuated Tiltrotor Hexacopter

arXiv:2211.06762v2 Announce Type: replace Abstract: Omnidirectional micro aerial vehicles (OMAVs) are more capable of doing environmentally interactive tasks due to their ability to exert full wrenche

researcharxiv-cs-ro

Adjoint Inversion Reveals Holographic Superposition and Destructive Interference in CNN Classifiers

arXiv:2604.27529v1 Announce Type: new Abstract: A foundational assumption in CNN interpretability -- that deep encoders suppress background pixels while classifiers merely select from a cleaned featur

AG-TAL: Anatomically-Guided Topology-Aware Loss for Multiclass Segmentation of the Circle of Willis Using Large-Scale Multi-Center Datasets

arXiv:2604.27357v1 Announce Type: cross Abstract: Accurate multiclass segmentation of the Circle of Willis (CoW) is essential for neurovascular disease management but remains challenging due to comple

AMGenC: Generating Charge Balanced Amorphous Materials

arXiv:2604.27613v1 Announce Type: new Abstract: Amorphous (disordered) materials are solids that have shown great potential in various domains, including energy storage, thermal management, and advanc

An Experimental Modular Instrument With a Haptic Feedback Framework for Robotic Surgery Training

arXiv:2604.27385v1 Announce Type: new Abstract: Robotic-assisted surgery offers significant clinical advantages but largely eliminates direct haptic feedback, increasing the risk of excessive tool-tis

researcharxiv-cs-ro

An Extended Evaluation Split for DeepSpaceYoloDataset

arXiv:2604.27593v1 Announce Type: cross Abstract: Recent technological advances in astronomy, particularly the growing popularity of smart telescopes for the general public, make it possible to develo

Anomaly Detection in Soil Heavy Metal Contamination Using Unsupervised Learning for Environmental Risk Assessment

arXiv:2604.27102v1 Announce Type: cross Abstract: Soil contamination by heavy metals poses a persistent environmental and public health concern in rapidly urbanising regions of Ghana, particularly at

Are DeepFakes Realistic Enough? Exploring Semantic Mismatch as a Novel Challenge

arXiv:2604.28022v1 Announce Type: new Abstract: Current DeepFake detection scenarios are mostly binary, yet data manipulation can vary across audio, video, or both, whose variability is not captured i

Beyond Gaussian Bottlenecks: Topologically Aligned Encoding of Vision-Transformer Feature Spaces

arXiv:2604.28122v1 Announce Type: new Abstract: Modern visual world modeling systems increasingly rely on high-capacity architectures and large-scale data to produce plausible motion, yet they often f

Beyond the Baseband: Adaptive Multi-Band Encoding for Full-Spectrum Bioacoustics Classification

arXiv:2604.27936v1 Announce Type: new Abstract: Animals hear and vocalize across frequency ranges that differ substantially from humans, often extending into the ultrasonic domain. Yet most computatio

Beyond the Training Distribution: Mapping Generalization Boundaries in Neural Program Synthesis

arXiv:2604.27551v1 Announce Type: cross Abstract: Large-scale transformers achieve impressive results on program synthesis benchmarks, yet their true generalization capabilities remain obscured by dat

Binary Spiking Neural Networks as Causal Models

arXiv:2604.27007v1 Announce Type: new Abstract: We provide a causal analysis of Binary Spiking Neural Networks (BSNNs) to explain their behavior. We formally define a BSNN and represent its spiking ac

BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning

arXiv:2604.27277v1 Announce Type: cross Abstract: Brain MRI underpins a wide range of neuroscientific and clinical applications, yet most learning-based methods remain task-specific and require substa

Budget-Constrained Online Retrieval-Augmented Generation: The Chunk-as-a-Service Model

arXiv:2604.26981v1 Announce Type: cross Abstract: Large Language Models (LLMs) have revolutionized the field of natural language processing. However, they exhibit some limitations, including a lack of

Calibrating Attribution Proxies for Reward Allocation in Participatory Weather Sensing

arXiv:2604.27944v1 Announce Type: new Abstract: Large-scale IoT weather sensing networks require incentive mechanisms to sustain participation, yet determining how much value individual data contribut

ClimateVID -- Social Media Videos Analysis and Challenges Involved

arXiv:2604.27968v1 Announce Type: new Abstract: The pervasive growth of digital content, specifically short videos on social media platforms, has significantly altered how topics are discussed and und

CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model

arXiv:2506.09110v3 Announce Type: replace Abstract: Electroencephalography (EEG) provides real-time insights into brain activity and supports diverse applications in neuroscience. While EEG foundation

Compliance versus Sensibility: On the Reasoning Controllability in Large Language Models

arXiv:2604.27251v1 Announce Type: cross Abstract: Large Language Models (LLMs) are known to acquire reasoning capabilities through shared inference patterns in pre-training data, which are further eli

Compositional Meta-Learning for Mitigating Task Heterogeneity in Physics-Informed Neural Networks

arXiv:2604.26999v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) approximate solutions of partial differential equations (PDEs) by embedding physical laws into the loss functio

Computing Equilibrium beyond Unilateral Deviation

arXiv:2604.28186v1 Announce Type: cross Abstract: Most familiar equilibrium concepts, such as Nash and correlated equilibrium, guarantee only that no single player can improve their utility by deviati

Context-Aware Graph Attention for Unsupervised Telco Anomaly Detection

arXiv:2604.27172v1 Announce Type: new Abstract: We propose C-MTAD-GAT, an unsupervised, context-aware graph-attention model for anomaly detection in multivariate time series from mobile networks. C-MT

Contextual Online Uncertainty-Aware Preference Learning for Human Feedback

arXiv:2504.19342v3 Announce Type: replace-cross Abstract: Reinforcement Learning from Human Feedback (RLHF) has become a pivotal paradigm in artificial intelligence to align large models with human pr

Continuous-tone Simple Points: An ell_0-Norm of Cyclic Gradient for Topology-Preserving Data-Driven Image Segmentation

arXiv:2604.28159v1 Announce Type: new Abstract: Topological features play an essential role in ensuring geometric plausibility and structural consistency in image analysis tasks such as segmentation a

Data-Efficient Indentation Size Effect Correction in Steels Using Machine Learning and Physics-Guided Augmentation

arXiv:2604.27775v1 Announce Type: cross Abstract: Shallow nanoindentation enables mechanical characterization of thin films, individual phases and other volume-constrained materials, but measured hard

Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing

arXiv:2604.27883v1 Announce Type: cross Abstract: In modern parametric model training, full-batch gradient descent (and its variants) suffers due to progressively stronger biasing towards the exact re

Decoupling the Benefits of Subword Tokenization for Language Model Training via Byte-level Simulation

arXiv:2604.27263v1 Announce Type: new Abstract: Subword tokenization is an essential part of modern large language models (LLMs), yet its specific contributions to training efficiency and model perfor

researcharxiv-cs-cl

Defeasible Conditional Obligation in a Two-tiered Preference-based Semantics (Extended Version)

arXiv:2604.26977v1 Announce Type: cross Abstract: In response to a concern raised by Horty, this paper develops a two-tiered, preference-based semantic framework for modeling defeasible conditional ob

Design and Characteristics of a Thin-Film ThermoMesh for the Efficient Embedded Sensing of a Spatio-Temporally Sparse Heat Source

arXiv:2604.28148v1 Announce Type: new Abstract: This work presents ThermoMesh, a passive thin-film thermoelectric mesh sensor designed to detect and characterize spatio-temporally sparse heat sources

researcharxiv-cs-ro

Differentiable latent structure discovery for interpretable forecasting in clinical time series

arXiv:2604.27967v1 Announce Type: new Abstract: Background: Timely, uncertainty-aware forecasting from irregular electronic health records (EHR) can support critical-care decisions, yet most approache

Differential Subgroup Discovery: Characterizing Where Two Populations Differ, and Why

arXiv:2604.27741v1 Announce Type: new Abstract: We study the problem of understanding where two populations differ within a feature space, which we formalize in the concept of a differential subgroup:

Diffusion-OAMP for Joint Image Compression and Wireless Transmission

arXiv:2604.27952v1 Announce Type: cross Abstract: Joint image compression and wireless transmission remain relatively underexplored compared to generic image restoration, despite its importance in pra

Do Sparse Autoencoders Capture Concept Manifolds?

arXiv:2604.28119v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are widely used to extract interpretable features from neural network representations, often under the implicit assumption

Dynamic Cluster Data Sampling for Efficient and Long-Tail-Aware Vision-Language Pre-training

arXiv:2604.27932v1 Announce Type: new Abstract: The computational cost of training a vision-language model (VLM) can be reduced by sampling the training data. Previous work on efficient VLM pre-traini

EAG-PT: Emission-Aware Gaussians and Path Tracing for Diffuse Indoor Scene Reconstruction and Editing

arXiv:2601.23065v2 Announce Type: replace-cross Abstract: Recent radiance-field-based reconstruction methods, such as NeRF and 3DGS, achieve high visual fidelity for indoor scenes, but often break dow

Ease of dependency distance minimization in star-like structures

arXiv:2604.28034v1 Announce Type: new Abstract: The syntactic structure of a sentence can be represented as a tree where edges indicate syntactic dependencies between words. When that structure is a s

researcharxiv-cs-cl

Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed

arXiv:2512.14067v2 Announce Type: replace-cross Abstract: Diffusion language models (dLMs) have emerged as a promising paradigm that enables parallel, non-autoregressive generation, but their learning

Efficient Multivector Retrieval with Token-Aware Clustering and Hierarchical Indexing

arXiv:2604.28142v1 Announce Type: cross Abstract: Multivector retrieval models achieve state-of-the-art effectiveness through fine-grained token-level representations, but their deployment incurs subs

EmDT: Embedding Diffusion Transformer for Tabular Data Generation in Fraud Detection

arXiv:2603.13566v2 Announce Type: replace-cross Abstract: Imbalanced datasets pose a difficulty in fraud detection, as classifiers are often biased toward the majority class and perform poorly on rare

Enabling Reconfiguration-Communication Overlap for Collective Communication in Optical Networks

arXiv:2510.19322v3 Announce Type: replace-cross Abstract: Collective communication (CC) is critical for scaling distributed machine learning (DML). The predictable traffic patterns of DML present a gr

Entropy-Dominated Temporal Vocal Dynamics as Digital Biomarkers for Depression Detection

arXiv:2604.26998v1 Announce Type: cross Abstract: Automated depression detection often relies on static aggregation of conversational signals, potentially obscuring clinically meaningful behavioral dy

Evaluating Epistemic Guardrails in AI Reading Assistants: A Behavioral Audit of a Minimal Prototype

arXiv:2604.27275v1 Announce Type: cross Abstract: Large language model (LLM) reading assistants are increasingly used in settings that require interpretation rather than simple retrieval. In these con

Evaluating TabPFN for Mild Cognitive Impairment to Alzheimer's Disease Conversion in Data Limited Settings

arXiv:2604.27195v1 Announce Type: new Abstract: Accurate prediction of conversion from Mild Cognitive Impairment (MCI) to Alzheimers Diseases (AD) is essential for early intervention, however, develop

EviMem: Evidence-Gap-Driven Iterative Retrieval for Long-Term Conversational Memory

arXiv:2604.27695v1 Announce Type: cross Abstract: Long-term conversational memory requires retrieving evidence scattered across multiple sessions, yet single-pass retrieval fails on temporal and multi

researcharxiv-cs-cl

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models

arXiv:2604.28149v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) have recently emerged as general-purpose forecasting models and show considerable potential for applications in en

Exploring the Adoption Intention in Using AI-Enabled Educational Tools Among Preservice Teachers in the Philippines: A Partial-Least Square Modeling

arXiv:2604.27346v1 Announce Type: cross Abstract: This study examines the factors influencing pre-service teachers' behavioral intention to use AI-enabled educational tools during their practicum, usi