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A Few More Tokens Ahead: Reinforcing Parallelism in Diffusion LLMs

arXiv:2610.18200v1 Announce Type: new Abstract: Parallel generation is widely regarded as an inherent advantage of diffusion large language models. Yet our fixed-quota evaluation of four representativ

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A Gated Catchment Hydrology Model (GCHM) for Physically-Interpretable Rainfall-Evapotranspiration-Runoff Simulation Across Diverse Hydroclimatic Regimes

DGX agent

arXiv:2610.14493v1 Announce Type: new Abstract: Recent advances in machine learning have improved rainfall-runoff prediction, yet most data-driven models remain difficult to interpret and do not expli

agentsarxiv-cs-lg

14 Oct 2026

A Generalized McDiarmid Inequality: Sample Reuse and Non-Uniform Unbounded Differences

arXiv:2610.17159v1 Announce Type: cross Abstract: We develop a novel generalization of McDiarmid's concentration inequality and use it to obtain a uniform law of large numbers result and error bounds

A Geometric Perspective on Reward Function Updates in Inverse Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2610.14041v1 Announce Type: new Abstract: Inverse Reinforcement Learning (IRL) is classically solved using Lagrangian optimisation, by jointly optimising a primal-dual problem with gradient desc

A Geometrical Approach to Constructing Neural Networks for Perfect Training-set Classification

arXiv:2610.17312v1 Announce Type: new Abstract: This paper proposes a method for constructing a neural network that achieves perfect classification of all samples in a given training set, without taki

A Hardware-Partitioned micro-ROS Mini-Vehicle for Operator-Supervised Neural Driving

arXiv:2610.15966v1 Announce Type: new Abstract: We present a low-cost miniature Ackermann vehicle for embedded neural-driving research, organized as a hardware-partitioned perceive-decide-act agent: a

safetyarxiv-cs-ro

A Hybrid Gaussian Process-Extreme Gradient Boosting Machine Learning Framework for Robust Knockdown Factor Prediction and Reliability-Based Design of Thin Spherical Shell Caps

model-releasesarxiv-cs-lg

arXiv:2610.15862v1 Announce Type: new Abstract: Elastic buckling remains a critical concern in the design of deep spherical shell caps, given that experiments reveal a significant reduction of critica

A Hybrid Kinematic GCN and Elastic Transformer for Efficient Indian Sign Language Recognition

arXiv:2610.14680v1 Announce Type: cross Abstract: Sign Language Recognition (SLR) presents complex challenges due to variable signing speeds and spatial intricacies. Specifically, Indian Sign Language

A Method for Exact Enforcement of Boundary Conditions on General Curved Triangular Domains: Algorithm and Application to Scientific Machine Learning

arXiv:2610.17392v1 Announce Type: cross Abstract: We present a method for enforcing exactly Dirichlet, Neumann, and Robin conditions on general triangular domains with arbitrarily curved boundaries. T

Agents

A Minimum Exact Disjunctive Basis for Two-Robot Solvability Profiles

arXiv:2610.17677v1 Announce Type: cross Abstract: We completely characterize the solvability profiles of tasks for two autonomous mobile robots in the plane under variable disorientation, chirality, a

agentsarxiv-cs-ro

A Multi-Task Deep Learning Framework for Pose-Invariant Face Recognition and Facial Landmark Localization

arXiv:2610.16849v1 Announce Type: new Abstract: Face recognition systems often experience performance degradation under large pose variations due to changes in facial appearance and visibility of disc

A Nonlinear Time-Series Theory for Constant-step SGD with Momentum

model-releasesarxiv-cs-lg

arXiv:2610.16034v1 Announce Type: cross Abstract: Constant-step stochastic gradient descent with momentum (SGDM) augments the parameter recursion with a momentum state that carries geometrically decay

A Note on Graphon-Signal Analysis of Graph Neural Networks

arXiv:2508.18564v2 Announce Type: replace Abstract: A recent paper, ``A Graphon-Signal Analysis of Graph Neural Networks'', by Levie, analyzed message passing graph neural networks (MPNNs) by embeddin

A Novel GPT-Based Framework for Anomaly Detection in System Logs

arXiv:2510.16044v2 Announce Type: replace-cross Abstract: Identification of anomalous events within system logs constitutes a pivotal element within the frame- work of cybersecurity defense strategies

A Persian Vision-Language-Action Dataset and Benchmark for Ambiguity- and Infeasibility-Aware Instruction-to-Plan Grounding

arXiv:2610.15666v1 Announce Type: new Abstract: Converting natural-language instructions into executable action plans conditioned on a scene image is a core capability for embodied human-robot interac

A physics-coupled graph neural operator for mid-plane six-component stress tensor field prediction in concrete penetration

arXiv:2610.16996v1 Announce Type: new Abstract: The penetration-resistant design of concrete structures requires the spatiotemporal evolution of the stress field within the target, whereas in design o

Applications

A Physics-Informed Hybrid Forward-Inverse Machine Learning Framework for High-Dimensional Sparse Recipe Reconstruction

arXiv:2610.14097v1 Announce Type: new Abstract: High-dimensional sparse recipe formulation in process industries involves nonlinear association of various covariates, bounded by sparsity constraints a

applicationsarxiv-cs-lg

A Plausible Future Is Not a Causal Future: Can Video Models Generate How the World Unfolds?

arXiv:2610.15562v1 Announce Type: new Abstract: Large-scale video generation models are increasingly viewed as a promising path toward world models, yet their ability to capture causally coherent phys

A Production-Grade, High-Efficiency Agentic RL Framework for Frontier LLMs with Validated Recipes

arXiv:2610.16352v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a critical phase in the post-training pipeline of large language models (LLMs). As the frontier of LLM capabi

A Rate Transfer Method: Convergence Rates in Stochastic Gradient Descent via Stochastic Calculus

arXiv:2610.18739v1 Announce Type: new Abstract: We develop a rate-transfer method that converts finite-time Lyapunov estimates for an associated stochastic differential equation (SDE) into finite-time

A Refresh Interval Does Not Fully Specify a Refresh Schedule: Learning-Rate-Dependent Placement in Kronecker-Preconditioned Language Model Training

arXiv:2610.18695v1 Announce Type: new Abstract: Kronecker-preconditioned optimizers recompute a cached curvature eigendecomposition only periodically, and implementations and adaptive methods control

A Reinforcement Learning Framework for Safety-Aware Haptic Shared Control in Surgical Robotics

model-releasesarxiv-cs-ro

arXiv:2610.15422v1 Announce Type: new Abstract: Haptic shared control in surgical robotics combines human-side and robot-side forces at a shared end effector while preserving operator involvement. How

A Sense of Proprioception in Language Models

arXiv:2610.17495v1 Announce Type: new Abstract: In humans, proprioception corresponds to the sense of self-movement or position, e.g. understanding the position of one's arm. This sense is often less

A Stochastic Analysis Perspective on Diffusion Models

arXiv:2610.14133v1 Announce Type: cross Abstract: Generative modelling involves two complementary tasks: learning a probabilistic approximation of an unknown data distribution from observations, and d

A Survey of Flow Matching in Reinforcement Learning

arXiv:2610.16275v1 Announce Type: new Abstract: Flow Matching (FM) has recently emerged as a principled and efficient generative modeling framework for reinforcement learning (RL), enabling expressive

A temporal graph dissimilarity measure capturing epidemic spreading behavior

arXiv:2610.16456v1 Announce Type: cross Abstract: Comparing temporal networks is a challenging problem in network analysis. Commonly adopted methods compare structural properties of temporal graphs an

A text-guided vision model for enhanced recognition of small instances

arXiv:2602.19503v2 Announce Type: replace Abstract: As drone-based object detection technology continues to evolve, the demand is shifting from merely detecting objects to enabling users to accurately

A Time-Synchronous Prequential Evaluation Framework for Next-Week Student Disengagement Prediction from Moodle LMS Logs

arXiv:2610.17490v1 Announce Type: new Abstract: Retrospective evaluation of early-warning models may not reflect information available when predictions are issued and outcomes become observable. We de

Tutorials

A Tutorial on Quantum Amplitude Embedding with Data Re-Uploading

arXiv:2610.17836v1 Announce Type: cross Abstract: Amplitude embedding lets a variational quantum model read many classical features with few qubits, but the model output is then only a quadratic form

tutorialsarxiv-cs-lg

A unified three-branch deep learning framework for automated detection and counting of wildlife in aerial imagery

arXiv:2610.17067v1 Announce Type: new Abstract: Automating aerial wildlife surveys requires reliable animal detection, consistent delineation of observation strips, and correction for repeated coverag

safetyarxiv-cs-cv

Accelerating Cross-Model LLM Inference via Attention Map Reuse

arXiv:2610.14688v1 Announce Type: new Abstract: LLM-augmented data workflows often involve multiple heterogeneous models operating over substantial shared context, such as schemas, tool specifications

Acceptable Misalignment

arXiv:2610.16881v1 Announce Type: cross Abstract: There is a specific challenge designers face in developing autonomous robots capable of open-ended learning. This challenge is how one can develop suc

safetyarxiv-cs-ro

Accounting for model error in ensemble variational data assimilation through learned generative dynamics

arXiv:2610.17333v1 Announce Type: cross Abstract: Many approaches have recently been proposed to combine data assimilation with machine learning for improved forecasts with geophysical models. Here, w

ACCRUE: Continual Off-Policy Reinforcement Learning for Robot Foundation Models

arXiv:2610.18596v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training improves robot foundation models (RFMs) beyond their demonstrations, but real-world deployment demands more:

Accuracy and Uncertainty in Machine Deception Detection (Research White Paper)

arXiv:2610.15314v1 Announce Type: new Abstract: A deception detector is only as useful as the trust its alarms deserve. Like a polygraph, detectors that read a language model's internal activations ca

ACED: Reference-Anchored Aggregation of Natural-Language and Executable Evidence for Mathematical Reasoning

arXiv:2610.16635v1 Announce Type: new Abstract: Natural-language self-consistency and executable programs provide complementary test-time evidence for mathematical reasoning, yet either channel may su

Across Viewpoints and Time: Trajectory-Generalizable Physical Attacks on World Models and Video Understanding Models

arXiv:2610.15343v1 Announce Type: new Abstract: World models and video understanding models are increasingly deployed in dynamic visual environments, yet their robustness to physical adversarial threa

safetyarxiv-cs-cv

Act4R: Action-conditioned 4D reconstruction for kinematics-free control

arXiv:2610.17462v1 Announce Type: new Abstract: Precise control of movement across various robotic embodiments is a longstanding challenge. Modeling complex robotic structures requires significant tim

safetyarxiv-cs-ro

Applications

Acting Through Registers

arXiv:2610.17638v1 Announce Type: new Abstract: World Action Models (WAMs) use generative visual representations to condition robot actions, yet how these representations organize action-relevant info

applicationsarxiv-cs-ro

Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation

arXiv:2404.01867v2 Announce Type: replace-cross Abstract: Efficiently tackling multiple tasks within complex environments, such as those found in robot manipulation, remains an ongoing challenge in ro

Active Neural Matter: A Finite-Window Response Framework for Physical Systems and Distributed AI Workflows

arXiv:2610.14549v1 Announce Type: new Abstract: Physical systems and distributed AI workflows can retain past information, receive delayed feedback and combine conflicting signals. These features pose

AD-GS: Anatomical Density-guided 3D Gaussian Splatting for Sparse-View Dental CBCT Reconstruction

arXiv:2610.14963v1 Announce Type: new Abstract: Sparse-view Cone-Beam Computed Tomography (CBCT) reconstruction is essential for reducing radiation dose and scan effort, but remains underconstrained d

AdaGamma: State-Dependent Discounting for Temporal Adaptation in Reinforcement Learning

arXiv:2605.06149v2 Announce Type: replace Abstract: The discount factor in reinforcement learning controls both the effective planning horizon and the strength of bootstrapping, yet most deep RL metho

Adaptive-Depth Is a Finishing Stage

arXiv:2610.14252v1 Announce Type: new Abstract: Looped transformers reuse the same layer multiple times, allowing inference compute to be adjusted without changing the model. Recent adaptive-depth met

Adaptive Interaction Network for Human Motion Prediction During Human-Robot Collaboration

arXiv:2610.16624v1 Announce Type: new Abstract: Human motion prediction during human-robot collaboration is critical for achieving safe and efficient interactions in shared environments. Unlike previo

Adaptive Look, Flexible Thought: Learning How and How Long to Think in Multimodal Reasoning

arXiv:2610.15810v1 Announce Type: new Abstract: The introduction of long chain-of-thought (CoT) reasoning and external tools has substantially improved the performance of multimodal large language mod

Adaptive Robust Confidence Sets in High Dimensions

arXiv:2610.15723v1 Announce Type: cross Abstract: We study adaptive confidence sets for mean vectors of multivariate Gaussians with identity covariance under Huber contamination when the contamination

Adaptive Role Assignment and Controlled Feature Reconstruction for Federated Image Semantic Communication

arXiv:2610.15623v1 Announce Type: new Abstract: Hybrid federated semantic communication enables user equipment (UEs) to contribute model updates or semantic features under a shared training framework.