Search: “papers”

Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data

arXiv:2606.00161v1 Announce Type: cross Abstract: The detection of intrusions in IoT-based networks poses challenges that cannot be overcome using traditional machine learning methods. Perhaps the big

researcharxiv-cs-ai

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InstructSAM: Segment Any Instance with Any Instructions

DGX agent

arXiv:2605.26102v2 Announce Type: replace Abstract: In this paper, we introduce InstructSAM, a unified and streamlined framework designed for multi-instance segmentation under arbitrary instructions.

model-releasesarxiv-cs-cv

2 Jun 2026

Agents

Interaction-Centered Intelligence: Toward Interaction as the Primary Unit of Analysis in Co-Creative AI and Human-AI Systems

arXiv:2606.00807v1 Announce Type: new Abstract: Traditional artificial intelligence has largely conceptualized intelligence as isolated computation occurring within bounded agents. Across classical AI

agentsarxiv-cs-ai

Introduction to Graph Neural Networks for Machine Learning Engineers

arXiv:2412.19419v2 Announce Type: replace-cross Abstract: Graph neural networks are deep neural networks designed for graphs with attributes attached to nodes or edges. The number of research papers i

researcharxiv-cs-ai

It does what it says on the tin: safe synthetic data from coarsened margins

arXiv:2606.02101v1 Announce Type: cross Abstract: This paper proposes a method of creating synthetic data (SD) that will have two important advantages for the user compared to other methods currently

Language-Native Materials Processing Design by Lightly Structured Text Database and Reasoning Large Language Model

model-releasesarxiv-cs-ai

arXiv:2509.06093v4 Announce Type: replace-cross Abstract: Materials synthesis procedures are predominantly documented as narrative text in papers, protocols, and laboratory records, placing them beyon

Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects

arXiv:2606.01950v1 Announce Type: cross Abstract: World models enable intelligent agents to predict the consequences of their actions on the environment. In this paper, we propose Multi Rigid Object G

researcharxiv-cs-cv

M^3 Scaling Law: Optimizing Multi-Epoch, Multi-Lingual, and Multi-Stage Training for Low-Resource Language Models

arXiv:2410.12325v2 Announce Type: replace Abstract: In this paper, we study a fundamental design problem in pretraining Large Language Models (LLMs) for low-resource language regimes. Existing works a

researcharxiv-cs-cl

Machine Learning-Based Bitcoin Trading Under Transaction Costs: Evidence From Walk-Forward Forecasting

arXiv:2606.00060v1 Announce Type: cross Abstract: This paper investigates whether machine learning forecasts of hourly BTC-USDT returns can be converted into economically meaningful trading performanc

Make Mechanistic Interpretability Auditable: A Call to Develop Guidelines via Continuous Collaborative Reviewing

arXiv:2606.00033v1 Announce Type: cross Abstract: While mechanistic interpretability (MI) has produced important insights into neural network internals, the field has yet to establish a standardized s

safetyarxiv-cs-ai

Markerless Augmented Reality Registration for Surgical Guidance: A Multi-Anatomy Clinical Accuracy Study

arXiv:2511.02086v2 Announce Type: replace Abstract: Purpose: In this paper, we develop and clinically evaluate a depth-only, markerless augmented reality (AR) registration pipeline on a head-mounted d

safetyarxiv-cs-cv

Measurement-Driven Early Warning of Reliability Breakdown in 5G NSA Railway Networks

arXiv:2511.08851v5 Announce Type: replace-cross Abstract: This paper presents a measurement-driven study of early warning for reliability breakdown events in 5G non-standalone (NSA) railway networks.

MipSLAM: Alias-Free Gaussian Splatting SLAM

arXiv:2603.06989v3 Announce Type: replace Abstract: This paper introduces MipSLAM, a frequency-aware 3D Gaussian Splatting (3DGS) SLAM framework capable of high-fidelity anti-aliased novel view synthe

researcharxiv-cs-cv

MixerSENet: A Lightweight Framework for Efficient Hyperspectral Image Classification

model-releasesarxiv-cs-cv

arXiv:2606.01700v1 Announce Type: new Abstract: In this paper, a novel framework, MixerSENet, is introduced for hyperspectral image (HSI) classification, designed to address the challenges of computat

Network Distributed Multi-Agent Reinforcement Learning for Consensus Control of Quadcopters

arXiv:2606.02107v1 Announce Type: cross Abstract: This paper proposes a Network Distributed Multi-Agent Reinforcement Learning (ND-MARL) framework for quadcopter consensus control. Compared to convent

safetyarxiv-cs-ai

Tutorials

PALTO: Physics-Informed Active Learning for Tri-Gate FinFET Design Optimization for Vertical Power Delivery

arXiv:2606.01265v1 Announce Type: cross Abstract: This paper demonstrates the effectiveness of machine learning-driven optimization for designing application-specific GaN tri-gate FinFETs in vertical

tutorialsarxiv-cs-ai

Position: Good Embodied Reward Models Need Bad Behavior Data

arXiv:2606.01036v1 Announce Type: new Abstract: This position paper argues that to obtain reliable embodied reward models, the community must invest in ``bad'' robot data: failed, suboptimal, error-pr

safetyarxiv-cs-ro

Position: Stop Preaching and Start Practising Data Frugality for Responsible Development of AI

arXiv:2602.19789v2 Announce Type: replace Abstract: This position paper argues that the machine learning community must move from preaching to practising data frugality for responsible artificial inte

safetyarxiv-cs-lg

Robust Integrated Planning and Control for Quadrotors in Dynamic Environments via NMPC with CBF Penalties

arXiv:2606.01038v1 Announce Type: new Abstract: This paper presents a new robust integrated planning and control (IPC) strategy for multirotor uncrewed aerial vehicles. We propose a nonlinear model pr

safetyarxiv-cs-ro

Spectra-Guided Neural Tucker Factorization

arXiv:2606.00584v1 Announce Type: cross Abstract: This paper proposes Spectra-Guided Neural Tucker Factorization (SG-NTF) for High-Dimensional and Incomplete (HDI) tensor completion. Circumventing dis

Tutorials

SpikeWFM: Spiking-Aided Wireless Foundation Model for Robust Channel Prediction

arXiv:2606.00120v1 Announce Type: cross Abstract: This paper proposes SpikeWFM, a novel hybrid architecture that integrates spiking neural networks (SNNs) with conventional artificial neural network (

tutorialsarxiv-cs-ai

Applications

Structure-Aware Consistency Priors for Shape from Polarization in Complex Media

arXiv:2606.00509v1 Announce Type: new Abstract: Recovering surface normals from single view polarization images in complex media remains challenging. This paper focuses on ice as a representative comp

applicationsarxiv-cs-cv

Structured Semantic Information Helps Retrieve Better Examples for In-Context Learning Applied to Few-Shot Relation Extraction

model-releasesarxiv-cs-cl

arXiv:2601.20803v2 Announce Type: replace Abstract: This paper presents several strategies to automatically obtain additional examples for in-context learning, effectively transforming relation extrac

Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees

arXiv:2404.07373v2 Announce Type: replace-cross Abstract: This paper presents a method to synthesize neural network controllers to maximize reward subject to the hard constraint that the feedback syst

Tiny Recursive Models for Solving the J2-Perturbed Lambert Problem

arXiv:2606.00895v1 Announce Type: cross Abstract: This paper presents a fast, recursive neural solver for the J2-perturbed Lambert problem based on Tiny Recursive Models (TRM), termed the TRM-Perturbe

ToolFG: Towards Well-Grounded Fine-Grained Image Classification

arXiv:2606.02518v1 Announce Type: new Abstract: Fine-grained image classification (FGIC) has broad applications and has attracted significant research attention. In this paper, we explore a novel para

safetyarxiv-cs-cv

Unveiling the Entropy Dynamics of Chain-of-Thought Reasoning

arXiv:2606.02020v1 Announce Type: new Abstract: This paper investigates the entropy dynamics of Chain-of-Thought (CoT) and uncovers a consistent two-phase structure: an Uncertainty Region of explorati

researcharxiv-cs-cl

Applications

WISE: A Multimodal Search Engine for Visual Scenes, Audio, Objects, Faces, Speech, and Metadata

arXiv:2602.12819v2 Announce Type: replace-cross Abstract: In this paper, we present WISE, an open-source audiovisual search engine which integrates a range of multimodal retrieval capabilities into a

applicationsarxiv-cs-cv

A Novel Evaluation Metric for Unsupervised Learning in AIS-Based Maritime Anomaly Detection: MADQI

arXiv:2605.30388v1 Announce Type: new Abstract: This paper introduces a new systematic framework for detecting anomalies in maritime Automatic Identification System (AIS) datasets. These anomalies inc

Actuator-Aware Inverse Kinematics with Joint-Limit Admissibility for Torque-Controlled Redundant Robots

arXiv:2605.31436v1 Announce Type: new Abstract: This paper proposes actuator-aware inverse kinematics for torque-controlled redundant robots under joint-limit constraints. In the considered architectu

researcharxiv-cs-ro

Adaptive Artificial Time-Delay Control with Barrier Lyapunov Constraints for Euler-Lagrange Robots

arXiv:2605.31405v1 Announce Type: new Abstract: This paper addresses the challenge of simultaneously compensating for state-dependent uncertainties and enforcing time-varying state constraints in Eule

safetyarxiv-cs-ro

Tutorials

Approximation and learning of anisotropic and mixed smooth functions by deep ReLU neural networks

arXiv:2605.31152v1 Announce Type: cross Abstract: This paper studies how efficiently deep ReLU neural networks can approximate and learn smooth functions. When the error is measured in L^p([0,1]^d) no

tutorialsarxiv-cs-lg

CodeGolf Bench: A Multi-Language Benchmark for Evaluating Concise Code Generation Capabilities of Large Language Models

model-releasesarxiv-cs-ai

arXiv:2605.30394v1 Announce Type: cross Abstract: This paper introduces Code Bench, a benchmark capable of evaluating Large Language Models (LLMs) concise code generation abilities in 60 programming l

DeblurSplat: SfM-free 3D Gaussian Splatting with Event Camera for Robust Deblurring

arXiv:2509.18898v2 Announce Type: replace Abstract: In this paper, we propose the first Structure-from-Motion (SfM)-free deblurring 3D Gaussian Splatting method via event camera, dubbed DeblurSplat. W

researcharxiv-cs-cv

Dynamical local Frechet curve regression in manifolds

arXiv:2505.05168v3 Announce Type: replace-cross Abstract: Under mild conditions, this paper derives a least-squares local linear Frechet curve predictor for response and regressor evaluated in a separ

EBuddy: a workflow orchestrator for industrial human-machine collaboration

arXiv:2603.28579v2 Announce Type: replace Abstract: This paper presents EBuddy, a voice-guided workflow orchestrator for natural human-machine collaboration in industrial environments. EBuddy targets

researcharxiv-cs-ro

From Evidence to Design: Developing an AI-Augmented UX Research Point of View for Digital Wellbeing in Emergency and Public Safety Contexts

arXiv:2605.31146v1 Announce Type: cross Abstract: This paper investigates how User Experience Research (UXR) methods can be combined with AI-supported analysis to develop clearer design direction for

safetyarxiv-cs-ai

High-Load-Density Electro-Permanent Magnetic Foot with Controllable Adhesion for Quadruped Wall-Climbing Robots

arXiv:2605.30849v1 Announce Type: new Abstract: To enable reliable climbing locomotion of quadruped robots on ferromagnetic surfaces, this paper presents a high-load-density electro-permanent magnetic

researcharxiv-cs-ro

Local Ai

Hyperspectral Image Classification using Spectral-Spatial Mixer Network

arXiv:2511.15692v2 Announce Type: replace Abstract: This paper introduces SS-MixNet, a lightweight and effective deep learning model for hyperspectral image (HSI) classification. The architecture inte

local-aiarxiv-cs-cv

Inference-Free Multimodal Learned Sparse Retrieval for Production-Scale Visual Document Search

model-releasesarxiv-cs-cv

arXiv:2605.30917v1 Announce Type: cross Abstract: As large-scale visual-document corpora such as arXiv papers and enterprise PDFs continue to grow, visual-document retrieval has gained increasing atte

Learning-Based Navigation for Indoor Mobile Robots

model-releasesarxiv-cs-ro

arXiv:2605.30468v1 Announce Type: new Abstract: This paper presents a learning-based navigation framework for indoor mobile robots. The proposed method combines a supervised neural global planner, tra

Local Ai

Neuro-Symbolic Predictive Process Monitoring

arXiv:2509.00834v2 Announce Type: replace Abstract: This paper addresses the problem of suffix prediction in Business Process Management (BPM) by proposing a Neuro-Symbolic Predictive Process Monitori

local-aiarxiv-cs-ai

Neuro-symbolic Syntactic Parsing: Shaping a Neural Network with the CYK Algorithm

model-releasesarxiv-cs-ai

arXiv:2605.31421v1 Announce Type: cross Abstract: In this paper, we show the possibility of a direct injection of algorithms into neural network architecture. We focus on a complex algorithm, that is,

Parameter-free Dynamic Regret: Time-varying Movement Costs, Delayed Feedback, and Memory

arXiv:2602.06902v2 Announce Type: replace Abstract: In this paper, we study dynamic regret in unconstrained online convex optimization (OCO) with movement costs. Specifically, we generalize the standa

Position: Evaluation of ECG Representations Must Be Fixed

arXiv:2602.17531v2 Announce Type: replace-cross Abstract: This position paper argues that current benchmarking practice in 12-lead ECG representation learning must be fixed to ensure progress is relia

researcharxiv-cs-ai

Post-Training Neural Network Pruning using Graph Curvature

arXiv:2601.16366v2 Announce Type: replace Abstract: This paper provides a fresh view of the neural network (NN) pruning problem through the lens of graph theory. To achieve effective pruning, we aim t

Reinforced sequential Monte Carlo for amortised sampling

arXiv:2510.11711v2 Announce Type: replace Abstract: This paper proposes a synergy of amortised and particle-based methods for sampling from distributions defined by unnormalised density functions. We

safetyarxiv-cs-lg

Representation Collapse in Sequential Post-Training of Large Language Models

arXiv:2605.30524v1 Announce Type: new Abstract: Large language models are now adapted through chains of post-training stages rather than through a single instruction-tuning pass. This paper studies wh

safetyarxiv-cs-lg