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arXiv:2606.20625v1 Announce Type: cross Abstract: LLM agents are promising for alpha mining via combining financial priors, symbolic reasoning, executable factor generation, and feedback-driven refine

agentsarxiv-cs-lg

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An Analysis of Untrained Deep Reservoir Networks for Audio Surveillance

DGX agent

arXiv:2606.22218v1 Announce Type: cross Abstract: In this paper, we investigate untrained recurrent models from the Reservoir Computing (RC) paradigm for audio surveillance, focusing on bidirectional

hardwarearxiv-cs-lg

23 Jun 2026

An approach with Visual and Tabular Mamba to multimodal medical data using Mixed Fusion

arXiv:2606.20738v1 Announce Type: new Abstract: This article presents a complementary approach for integrating multimodal medical data in cancer classification, based on state space models represented

An Effective Strategy for Modeling Score Ordinality and Non-uniform Intervals in Automated Speaking Assessment

arXiv:2509.03372v3 Announce Type: replace-cross Abstract: A recent line of research on automated speaking assessment (ASA) has benefited from self-supervised learning (SSL) representations, which capt

An Efficient and Effective Architecture for Large-Scale Traffic Prediction via Geometry-Adaptive Square Partitioning

arXiv:2606.21072v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems and urban-scale decision making. Despite the effectiveness of mainstream neural-

applicationsarxiv-cs-lg

An Empirical Study of OpenPangu Quantization on Ascend NPUs

arXiv:2606.21257v1 Announce Type: new Abstract: OpenPangu models are attractive targets for private and domestic large-language-model deployment, yet their robustness under aggressive post-training qu

An intuitive rearranging of the Yates covariance decomposition for probabilistic verification of forecasts with the Brier score

arXiv:2603.05544v2 Announce Type: replace-cross Abstract: Proper scoring rules are essential for evaluating probabilistic forecasts. We propose a simple algebraic rearrangement of the Yates covariance

An LLM-Explainable DRL Framework for Passenger-Directed Autonomous Driving

arXiv:2606.20640v1 Announce Type: cross Abstract: Autonomous vehicles offer the potential for safer and more efficient mobility, yet public trust remains limited due to the lack of transparency in the

Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms

arXiv:2606.20617v1 Announce Type: cross Abstract: Student attrition represents a significant challenge for higher education institutions because it impacts both academic results and financial viabilit

applicationsarxiv-cs-lg

Local Ai

Anatomically Consistent TMJ Disc Segmentation via Semantic Anchoring and Clinical Priors

arXiv:2606.21177v1 Announce Type: cross Abstract: Segmenting the temporomandibular joint (TMJ) disc from MRI is essential for accurate diagnosis of internal derangement, yet it remains unreliable in p

local-aiarxiv-cs-cv

Anticipating the Optimism Gap: Predicting Distribution-Shift Degradation of RF-Impairment Detectors from In-Distribution Statistics

arXiv:2606.22054v1 Announce Type: cross Abstract: Detectors for GNSS radio-frequency impairments (jamming, spoofing, multipath) are usually reported with a single AUC measured on the distribution they

Any-Body Guard: Universal Safeguarding for Manipulation Policies via Action Masking

arXiv:2606.22278v1 Announce Type: cross Abstract: Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing

APEX: Action Priors Enable Efficient Exploration for Robust Motion Tracking on Legged Robots

arXiv:2505.10022v4 Announce Type: replace Abstract: Learning natural, animal-like locomotion from demonstrations has become a core paradigm in legged robotics. While motion tracking can reproduce refe

safetyarxiv-cs-ro

Approximating velocity fields with planted attractors via Neural-ODEs for classification purposes

arXiv:2606.23550v1 Announce Type: cross Abstract: In this work, Neural ODEs equipped with a curated collection of equilibrium points have been successfully employed for classification tasks.The plante

Arbor: Explicit Geometric Conditioning for Controllable 3D Asset Generation

arXiv:2606.23514v1 Announce Type: new Abstract: Text and image conditioned 3D models now generate convincing assets, but they still offer little direct control over the space an object should occupy o

Arc-Length Parameterized Interpolating Splines

arXiv:2606.21209v1 Announce Type: cross Abstract: We present an iterative algorithm to compute an arc-length parameterized spline interpolating a set of points. This differs from other methods where t

ARCO-Mars: A Unified Cloud-Optimized Archive of Mars Atmosphere Reanalysis

arXiv:2606.21701v1 Announce Type: cross Abstract: Long-term records of the Martian atmosphere based on general circulation models and reanalysis of atmospheric state variables are important to underst

ARGUSTRACK: A Multi-View Annotation System for Multi-Object Tracking

arXiv:2606.20687v1 Announce Type: new Abstract: Multi-Camera Multi-Target (MCMT) tracking has emerged as a critical capability for applications ranging from autonomous driving to animal behavior monit

safetyarxiv-cs-cv

ARP: Enhancing Quantized Skill Abstractions via Visual Alignment and Iterative Refinement for Robotic Manipulation

arXiv:2606.22480v1 Announce Type: new Abstract: Learning visuomotor policies for long-horizon manipulation remains a fundamental challenge. Recent skill-based imitation learning methods based on discr

safetyarxiv-cs-ro

Artic-O: End-to-End Articulated Object Reconstruction via Latent Geometry Learning

arXiv:2606.21938v1 Announce Type: new Abstract: Reconstructing articulated objects from sparse images requires recovering complete geometry, movable parts, and motion parameters. Recent methods typica

ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software

arXiv:2408.02153v2 Announce Type: replace-cross Abstract: Achieving reproducibility, quantity, and diversity in vulnerability datasets has long been viewed as an inherent three-way trade-off, where im

applicationsarxiv-cs-lg

ASC-SW: A Lightweight Atrous Strip Convolution Network for DLOs Segmentation on Edge mobile Robots

arXiv:2507.12744v4 Announce Type: replace Abstract: Detecting deformable linear objects (DLOs), such as floor cables, is essential for safe mobile robot navigation but remains challenging due to obliq

applicationsarxiv-cs-ro

ASCII Art Turns LLMs into VLA Controllers

model-releasesarxiv-cs-cv

arXiv:2606.21470v1 Announce Type: cross Abstract: Vision--Language--Action (VLA) controllers are often built by extending vision--language models (VLMs) with action supervision, relying on multimodal

Assistron: Bayesian Shared Autonomy with Off-the-shelf Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2606.23147v1 Announce Type: new Abstract: We propose Assistron, a shared autonomy model that leverages Vision-Language-Action (VLA) models to assist the user in daily activities. Our approach is

Associative Memory for Non-Stationary Environments: A Self-Sizing Generalization of Hopfield Networks

arXiv:2507.10443v3 Announce Type: replace-cross Abstract: The Hopfield network made associative memory (AM) the model system of neural computation, but it solves the problem only for a stationary worl

Local Ai

ASTRA: A Scalable Next-Generation ATCO Training Simulator with Autonomous Simpilots

arXiv:2606.18319v2 Announce Type: replace Abstract: Air Traffic Control Operators (ATCOs) are vital in ensuring the safe, orderly, and efficient flow of air traffic, yet training capacity is constrain

local-aiarxiv-cs-lg

Tutorials

Asymmetric physics enables efficient learning in quadrupedal robot swarms

arXiv:2606.23153v1 Announce Type: new Abstract: Animal collectives navigate cluttered environments through local coordination, yet robot swarms still struggle to reproduce this capability in the physi

tutorialsarxiv-cs-ro

Asymptotic Signal Subspace Recovery in Softmax Attention Models

arXiv:2606.22406v1 Announce Type: new Abstract: Attention mechanisms have demonstrated remarkable empirical success in identifying relevant information from large collections of tokens, yet the theore

Atomistic Language Models Understand and Generate Materials

arXiv:2606.21395v1 Announce Type: new Abstract: Atomistic structure and natural language have long been modeled separately, with language models either calling atomistic models as tools or being fine-

Attacking the Trusted Imagination: Oracle-Level Integrity Attacks on Imagine-then-Act World Models

arXiv:2606.22966v1 Announce Type: new Abstract: Many recent vision-language-action (VLA) policies adopt an imagine-then-act design. A world-action model (WAM) first imagines a short future as a latent

Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation

arXiv:2604.01989v3 Announce Type: replace Abstract: Like a body at rest that stays at rest, we find that visual attention in multimodal large language models (MLLMs) exhibits pronounced inertia, remai

Attention mechanism for scalable mesh-based neural surrogates of free-surface fluids

arXiv:2606.23251v1 Announce Type: cross Abstract: High-fidelity simulations of free-surface flows using Lagrangian methods such as the Particle Finite Element Method (PFEM) are computationally demandi

Attention-Spectrum Regularization for Replay-Free Continual Multimodal LLMs

arXiv:2606.23063v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly required to adapt to non-stationary streams of visual domains, question types, and user instru

AutoDex: An Automated Real-World System for Dexterous Grasping Data Collection

arXiv:2606.23689v1 Announce Type: cross Abstract: Learning robust dexterous grasping requires real-world data that records the physical outcomes of grasp attempts. Such data is hard to obtain at scale

Automated sign detection across the Electronic Babylonian Library: A large-scale dataset and end-to-end cuneiform OCR pipeline

arXiv:2606.22608v1 Announce Type: new Abstract: Learning to read cuneiform tablets is an extremely demanding task; consequently, of the roughly half million excavated tablets, only a small fraction ha

Agents

Autonomous and Self-Adapting System for Synthetic Media Detection and Attribution

arXiv:2504.03615v2 Announce Type: replace Abstract: Rapid advances in generative AI have enabled the creation of highly realistic synthetic images, which, while beneficial in many domains, also pose s

agentsarxiv-cs-cv

Agents

Autonomous Subsea Cable Search and Tracking with Graph-Optimised Priors and Visual Tracking

arXiv:2606.23606v1 Announce Type: cross Abstract: Global communications rely on subsea cable infrastructure that remains vulnerable to damage from natural hazards and human activity. Autonomous underw

agentsarxiv-cs-cv

AwakeForest: An Interactive Geospatial Platform for Large-Scale Forest Imagery

arXiv:2606.23542v1 Announce Type: new Abstract: Forest imagery analysis often involves multiple tightly coupled vision tasks, which must be performed under substantial variation in geographic regions,

Hardware

BAC-JEPA: Label-Efficient Breast Arterial Calcification Segmentation via Synthetic Mammography-Guided Supervision

arXiv:2606.22089v1 Announce Type: new Abstract: Breast arterial calcification (BAC) on screening mammograms is an emerging cardiovascular risk biomarker, but quantitative use requires reproducible seg

hardwarearxiv-cs-cv

Backpropagating Through Simulation: Analytic Policy Gradients for Sample and Learning Efficient Differentiable Continuous Control

arXiv:2606.21525v1 Announce Type: new Abstract: Model-free reinforcement learning algorithms such as Proximal Policy Optimization (PPO) treat the environment as a black box, estimating policy gradient

BadDreamer: Transferable Backdoor Attacks against Video World Models for Autonomous Driving

arXiv:2606.21172v1 Announce Type: new Abstract: Video world models are increasingly used in autonomous driving to forecast future scene evolution and provide future-aware spatio-temporal representatio

safetyarxiv-cs-cv

Balancing Performance and Diversity in GRPO Autoregressive Text-to-Image Post-Training

arXiv:2606.21498v1 Announce Type: cross Abstract: Autoregressive text-to-image (T2I) generation has recently advanced rapidly, yet aligning generated images with human preferences remains challenging.

BARD-MARL: Byzantine-Agent Detection for Learned Communication in Multi-Agent Reinforcement Learning

arXiv:2606.20701v1 Announce Type: cross Abstract: Learned communication improves coordination in cooperative multi-agent reinforcement learning, but it also creates a trust problem: a trained policy m

Tutorials

BASIL: Bayesian Application for Scientific Iteration and Learning

arXiv:2606.21092v1 Announce Type: new Abstract: We introduce BASIL, a user-friendly desktop application for process optimization. BASIL employs a Bayesian approach, incorporating special acquisition f

tutorialsarxiv-cs-lg

Hardware

BatchGen: An Architecture for Scalable and Efficient Batch Inference

arXiv:2606.21712v1 Announce Type: cross Abstract: Batch inference has become a central mode of AI computation, yet existing inference engines still rely on execution models designed for interactive se

hardwarearxiv-cs-lg

BayesFP: Posterior Estimation for Flow-Based Policies via Feynman-Kac Sampling

arXiv:2606.21014v1 Announce Type: new Abstract: Robots must generate trajectories that remain faithful to learned expert behavior while satisfying safety constraints and task-specific objectives speci

safetyarxiv-cs-ro

Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models

arXiv:2606.22188v1 Announce Type: new Abstract: Large multi-modal language models are increasingly deployed in high-stakes domains, making well-calibrated uncertainty essential. Traditional Bayesian m

Tutorials

Bayesian Model Averaging under Predictor Redundancy via Density-Ratio Posterior Compression

arXiv:2606.21080v1 Announce Type: cross Abstract: Bayesian model averaging in support-indexed regression induces a posterior distribution over active predictor supports. Under predictor redundancy, po

tutorialsarxiv-cs-lg