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arXiv:2605.16895v1 Announce Type: cross Abstract: End-to-end LLM trading agents have moved quickly from research curiosity to a small ecosystem of named systems, including FinCon, FinMem, TradingAgent

agentsarxiv-cs-ai

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The MixCount Dataset: Bridging the Data Gap for Open-Vocabulary Object Counting

DGX agent

arXiv:2605.18063v1 Announce Type: new Abstract: Object counting is a foundational vision task with over a decade of dedicated research, yet state-of-the-art models still fail systematically in the mix

model-releasesarxiv-cs-cv

19 May 2026

Threats to Arabic Handwriting Recognition: Investigating Black-Box Adversarial Attacks on embedded ConvNet models

model-releasesarxiv-cs-cv

arXiv:2605.18058v1 Announce Type: new Abstract: Arabic handwriting recognition (AHR) has made significant progress with deep learning models. AHR research has largely focused on performance, with secu

Time-Efficient Hybrid Hyperparameter Tuning Approach for Cardiovascular Disease Classification

arXiv:2411.18234v2 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are any serious illness of the heart, which require accurate diagnosis to prevent fatal consequences. Hyperpara

TPV: Parameter Perturbations Through the Lens of Test Prediction Variance

arXiv:2512.11089v4 Announce Type: replace-cross Abstract: We introduce test prediction variance (TPV)--the first-order sensitivity of a trained model's outputs to parameter perturbations--as a unifyin

Transformer-Based MCS Prediction for 5G Multicast-Broadcast Services (MBS)

arXiv:2605.16735v1 Announce Type: cross Abstract: The deployment of 5G Multicast-Broadcast Services (MBS) is emerging as a critical technology for spectral-efficient UHD content delivery and serving a

TusoAI: Agentic Optimization for Scientific Methods

arXiv:2509.23986v2 Announce Type: replace Abstract: Scientific discovery is often slowed by the manual development of computational tools needed to analyze complex experimental data. Building such too

UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models

arXiv:2605.16690v1 Announce Type: new Abstract: Heterogeneous LoRA-rank methods address system heterogeneity in federated fine-tuning of foundation models by assigning client-specific ranks based on c

Universal Graph Backdoor Defense: A Feature-based Homophily Perspective

arXiv:2605.16815v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have achieved remarkable success in relational learning. However, their vulnerability to graph backdoor attacks (GBAs) po

Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving

arXiv:2602.22801v2 Announce Type: replace-cross Abstract: Diffusion models have become a popular choice for decision-making tasks in robotics, and more recently, are also being considered for solving

Unleashing Vision Transformer Potential In Image Quality Assessment via Global-Local Adaptive Interaction

arXiv:2605.17748v1 Announce Type: new Abstract: In the field of Blind Image Quality Assessment (BIQA), accurately predicting the perceptual quality of authentically distorted images remains highly cha

researcharxiv-cs-cv

Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning

arXiv:2510.02590v2 Announce Type: replace Abstract: The use of target networks is a popular approach for estimating value functions in deep Reinforcement Learning (RL). While effective, the target net

Variational Optimality of Follmer Processes in Generative Diffusions

arXiv:2602.10989v2 Announce Type: replace-cross Abstract: We construct and analyze generative diffusions that transport a point mass to a prescribed target distribution over a finite time horizon usin

WEBSERV: A Full-Stack and RL-Ready Web Environment for Training Web Agents at Scale

model-releasesarxiv-cs-cl

arXiv:2510.16252v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for web agents demands environments that are both effective for evaluation and efficient enough for large-scale on

When Fireflies Cluster; Enhancing Automatic Clustering via Centroid-Guided Firefly Optimization

arXiv:2605.18460v1 Announce Type: new Abstract: This work presents a novel variant of the Firefly Algorithm (FA) for data clustering, addressing limitations of traditional methods like K-Means that st

Tutorials

When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables

arXiv:2509.17680v2 Announce Type: replace Abstract: Table question answering (TableQA) is a fundamental task in natural language processing (NLP). The strong reasoning capabilities of large language m

tutorialsarxiv-cs-cl

White-Box Sensitivity Auditing with Steering Vectors

arXiv:2601.16398v2 Announce Type: replace-cross Abstract: Algorithmic audits are essential tools for examining systems for properties required by regulators or desired by operators. Current audits of

safetyarxiv-cs-cl

WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform

model-releasesarxiv-cs-cv

arXiv:2605.17912v1 Announce Type: cross Abstract: World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about envir

Hardware

A Unified Non-Parametric and Interpretable Point Cloud Analysis via t-FCW Graph Representation

arXiv:2605.15475v1 Announce Type: new Abstract: We introduce an empowered transposed Fully Connected Weighted (t-FCW) graph representation to embed point clouds into a metric space. While original t-F

hardwarearxiv-cs-cv

An Algebraic Exposition of the Theory of Dyadic Morality

arXiv:2605.16153v1 Announce Type: new Abstract: This paper provides an algebraic exposition of the theory of dyadic morality (TDM), a psychological model of moral judgment grounded in a simple two-nod

Agents

Autonomous Intelligent Agents for Natural-Language-Driven Web Execution with Integrated Security Assurance

arXiv:2605.15281v1 Announce Type: cross Abstract: Modern web test suites rot. A UI refactor breaks locators, a timing change causes race conditions, and within weeks developers abandon the suite entir

agentsarxiv-cs-ai

Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty

arXiv:2507.16806v2 Announce Type: replace-cross Abstract: When language models (LMs) are trained via reinforcement learning (RL) to generate natural language 'reasoning chains', their performance impr

Beyond Content: A Comprehensive Speech Toxicity Dataset and Detection Framework Incorporating Paralinguistic Cues

arXiv:2605.15984v1 Announce Type: cross Abstract: Toxic speech detection has become a crucial challenge in maintaining safe online communication environments. However, existing approaches to toxic spe

Beyond Objective-Based Improvement: Stationarity-Aware Expected Improvement for Bayesian Optimization

arXiv:2601.21357v2 Announce Type: replace Abstract: Bayesian Optimization (BO) is a principled framework for optimizing expensive black-box functions, with Expected Improvement (EI) among its most wid

Can We Trust AI-Inferred User States. A Psychometric Framework for Validating the Reliability of Users States Classification by LLMs in Operational Environments

arXiv:2605.15734v1 Announce Type: new Abstract: The use of large language models to assess user states in conversational and adaptive systems is based on the assumption that the metrics used for such

Centralized vs Decentralized Federated Learning: A trade-off performance analysis

arXiv:2605.16089v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for collaborative model training across distributed edge devices while preserving data pri

Constrained MPC-Based Motion Planning for Morphing Quadrotors in Ultra-Narrow Passages under Limited Perception

arXiv:2605.15999v1 Announce Type: new Abstract: This paper introduces a motion planning framework to plan morphology and trajectory for morphing quadrotors under extremely constrained environments. We

safetyarxiv-cs-ro

Context-aware Entity-Relation Extraction for Threat Intelligence Knowledge Graphs

arXiv:2605.15904v1 Announce Type: new Abstract: Cybersecurity Knowledge Graphs (CKGs) unify diverse Cyber Threat Intelligence (CTI) sources into structured, queryable formats, offering scalable soluti

CTF4Nuclear: Common Task Framework for Nuclear Fission and Fusion Models

arXiv:2605.15549v1 Announce Type: cross Abstract: The demand for clean energy is ever increasing, with new nuclear technologies presenting a complementary solution to renewable energies. However, desi

Tutorials

Curriculum Learning of Physics-Informed Neural Networks based on Spatial Correlation

arXiv:2605.15254v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) combine deep learning with physical constraints for solving partial differential equations (PDEs), and are wide

tutorialsarxiv-cs-lg

Decentralized LoRA augmented transformer with multi-scale feature learning for secured eye diagnosis

model-releasesarxiv-cs-cv

arXiv:2505.06982v3 Announce Type: replace Abstract: Accurate and privacy-preserving diagnosis of ophthalmic diseases remains a critical challenge in medical imaging, particularly given the limitations

Tutorials

Deep Learning Alternatives of the Kolmogorov Superposition Theorem

arXiv:2410.01990v3 Announce Type: replace Abstract: This paper explores alternative formulations of the Kolmogorov Superposition Theorem (KST) as a foundation for neural network design. The original K

tutorialsarxiv-cs-lg

Detecting Heel Strike and toe off Events Using Kinematic Methods and LSTM Models

arXiv:2503.00794v2 Announce Type: replace Abstract: Accurate gait event detection is crucial for gait analysis, rehabilitation, and assistive technology, particularly in exoskeleton control, where pre

safetyarxiv-cs-ro

DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection

model-releasesarxiv-cs-cl

arXiv:2605.15518v1 Announce Type: new Abstract: The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misus

Deterministic Coreset for Lp Subspace

arXiv:2601.00361v3 Announce Type: replace-cross Abstract: We introduce the first iterative algorithm for constructing a arepsilon-coreset that guarantees deterministic ell_p subspace embedding for any

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space

arXiv:2605.15368v1 Announce Type: new Abstract: Group-convolutional neural networks (GCNNs) are among the most important methods for introducing symmetry as an inductive bias in deep learning: In each

safetyarxiv-cs-cv

EgoExo-WM: Unlocking Exo Video for Ego World Models

arXiv:2605.15477v1 Announce Type: new Abstract: Egocentric world models present a promising direction for enabling agents to predict and plan, but their performance is constrained by the limited avail

safetyarxiv-cs-cv

Embracing Biased Transition Matrices for Complementary-Label Learning with Many Classes

arXiv:2605.15586v1 Announce Type: cross Abstract: Complementary-label learning (CLL) is a weakly supervised paradigm where instances are labeled with classes they do not belong to. Despite a decade of

EndoGSim: Physics-Aware 4D Dynamic Endoscopic Scene Simulations via MLLM-Guided Gaussian Splatting

arXiv:2605.16022v1 Announce Type: new Abstract: In robot-assisted minimally invasive surgery, high-fidelity dynamic endoscopic scene reconstruction and simulation are crucial to enhancing downstream t

researcharxiv-cs-cv

Entropy-Based Characterisation of the Polarised Regime in Latent Variable Models

arXiv:2605.15965v1 Announce Type: new Abstract: Variational Autoencoders (VAEs) often exhibit a polarised regime in which latent variables separate into active, passive, and mixed subsets. Existing cr

f-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data

arXiv:2605.15417v1 Announce Type: cross Abstract: In GFlowNets and variational inference, it has been shown that the mean square error between target and model log probabilities is an effective, low v

Fair outputs, Biased Internals: Causal Potency and Asymmetry of Latent Bias in LLMs for High-Stakes Decisions

arXiv:2605.15217v1 Announce Type: new Abstract: Instruction-tuned language models exhibit behavioural fairness in high-stakes decisions while retaining biased associations in their internal representa

Hardware

FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization

arXiv:2605.15824v1 Announce Type: new Abstract: Human-centric video customization, particularly at the garment level, has shown significant commercial value. However, existing approaches cannot suppor

hardwarearxiv-cs-cv

Federated Learning of Spiking Neural Networks under Heterogeneous Temporal Resolutions

arXiv:2605.15355v1 Announce Type: new Abstract: Spiking neural networks (SNNs) are biologically inspired energy-efficient models that use sparse binary spike-based communication between neurons, makin

From Layers to Networks: Comparing Neural Representations via Diffusion Geometry

arXiv:2605.15901v1 Announce Type: new Abstract: Diffusion geometry is a manifold learning framework that uses random walks defined by Markov transition matrices to characterize the geometry of a datas

From Model Design to Organizational Design: Complexity Redistribution and Trade-Offs in Generative AI

arXiv:2506.22440v2 Announce Type: replace-cross Abstract: This paper introduces the Generality-Accuracy-Simplicity (GAS) framework to analyze how large language models (LLMs) are reshaping organizatio

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks

arXiv:2605.15328v1 Announce Type: new Abstract: Fully Connected Neural Networks (FCNNs) are often regarded as simple and intuitive architectures, yet they serve as the foundation for more complex mode

GenShield: Unified Detection and Artifact Correction for AI-Generated Images

arXiv:2605.16122v1 Announce Type: cross Abstract: Diffusion-based image synthesis has made AI-generated images (AIGI) increasingly photorealistic, raising urgent concerns about authenticity in applica