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A Differentiable 3D Scene Graph Metric via Contextual Hellinger Triplet Geometry

arXiv:2610.17705v1 Announce Type: new Abstract: 3D scene graph prediction is commonly supervised with local object and predicate classification losses. Although effective for slot-wise label predictio

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A Few More Tokens Ahead: Reinforcing Parallelism in Diffusion LLMs

DGX agent

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

safetyarxiv-cs-lg

14 Oct 2026

Agents

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

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

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