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arXiv:2610.14915v1 Announce Type: new Abstract: Developing terminal-based agents for long-horizon execution demands synthetic tasks that tightly couple complex instructions with authentic, interactive

agentsarxiv-cs-ai

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World Models Need a Physical Registry: Learning Internal Predictive States for Physically Plausible World Models

DGX agent

arXiv:2610.16365v1 Announce Type: new Abstract: Video world models must generate physically plausible futures, not just realistic frames. Existing approaches typically use semantic, physical, or predi

tutorialsarxiv-cs-ai

15 Oct 2026

WorldMemBench: A Comprehensive Benchmark for Memory of Video World Models

arXiv:2610.19063v1 Announce Type: new Abstract: As video models enable longer and more realistic interactive experiences, maintaining a world consistent with its history becomes essential. This requir

XL-SafetyBench: A Country-Grounded Cross-Cultural Benchmark for LLM Safety and Cultural Sensitivity

model-releasesarxiv-cs-ai

arXiv:2605.05662v2 Announce Type: replace-cross Abstract: Current LLM safety benchmarks are predominantly English-centric and often rely on translation, failing to capture country-specific harms. More

Industry

Your secrets aren’t safe with this cute robot toy — they’re on Chinese servers ready to be hacked

There's a new digital pet in town - a cute little marshmallow of a robot that can change its cartoony expressions to match your mood. But if you or your kids talk to 'Eiliko' over Wi-Fi, it'll phone h

industrythe-verge-ai

Your Transformer Is Secretly Elastic

arXiv:2610.20588v1 Announce Type: new Abstract: Scaling up transformers has produced models with broad capabilities, deployed across heterogeneous hardware and fluctuating workloads. Yet, model famili

176 t/s decode and 6,450 t/s prefill with Q4 Qwen-3.8 Flash-Next on 2xR9700 + 64GB DDR5 using Deadcode's Radiance engine

model-releasesr-localllama

https://preview.redd.it/kudj7xii5ivh1.png?width=1508&format=png&auto=webp&s=07712e81310b81aceb2cf8f4d8a7c2eadeb0c304 Just built a new PC, full parts list is here. I am using Deadcode's Radiance infere

Applications

1Step-WAM: Your World Action Model but Faster using 1-Step Action Generation

arXiv:2610.15625v1 Announce Type: new Abstract: World Action Models (WAMs) unify visual world modeling and action generation, yet their real-world deployment is heavily bottlenecked by iterative actio

applicationsarxiv-cs-cv

3D Gaussian Splatting for Fine-grained Urban Scene Reconstruction via Semantic-guided Density Control and Loss Design

arXiv:2610.16292v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has been becoming a promising 3D reconstruction technique because of its advantage of high-fidelity rendering effect with h

3D-VITAL: Visibility-aware Identity Training from Artificial Liftings of 3D Reconstruction model for Cross-View Object Re-Identification

arXiv:2610.16692v1 Announce Type: new Abstract: We address the Cross-View Object Re-Identification (ReID) task, aiming to match identities across drastically different viewpoints. We focus on Single-V

3DXTalker: Unifying Identity, Lip Sync, Emotion, and Spatial Dynamics in Expressive 3D Talking Avatars

arXiv:2602.10516v4 Announce Type: replace Abstract: Audio-driven 3D talking avatar generation is increasingly important in virtual communication, digital humans, and interactive media, where avatars m

4LC: 4D Latent Cache for Efficient Conditioning in Dynamic World Modeling

arXiv:2610.17625v1 Announce Type: new Abstract: For video generation in dynamic world modeling, observed static and dynamic content should be efficiently reused to provide conditions for repeated gene

A 35B multimodal model running on a phone with ~3GB memory? MiniCPM-V 4.7 demo is pretty wild

model-releasesr-localllama

Just saw this demo from OpenBMB for MiniCPM-V 4.7, and the on-device capability is pretty impressive. A 35B-A3B MoE vision-language model running locally on mobile devices is already interesting, but

A 4-Qubit Variational Quantum Classifier for Sequence-Specific Classification of DNMT3A and DNMT3B Flanking Methylation Preferences

arXiv:2610.15998v1 Announce Type: new Abstract: DNA methylation is a critical epigenetic modification that regulates gene expression and genome stability, primarily catalyzed by the DNA methyltransfer

A Behavior-first approach to Multi-Intention Inverse Reinforcement Learning

arXiv:2602.07496v2 Announce Type: replace Abstract: Inverse Reinforcement Learning (IRL) seeks to infer reward functions from expert demonstrations. When demonstrations originate from multiple experts

A Bethe-Ansatz Source of Early Token Correlations: A marginal-preserving construction for parallel proposals

arXiv:2610.16781v1 Announce Type: cross Abstract: Parallel token proposals in language-model decoding need a joint law, not merely accurate token marginals. We construct a family of coordinate-Bethe-a

A CaLLM Judge is a Better Judge: Mitigating Bias in LLM-as-a-judge

arXiv:2610.18108v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as judges to predict which of two candidate answers a human evaluator would prefer, providing a scala

Local Ai

A Comprehensive Review on RNA Subcellular Localization Prediction

arXiv:2504.17162v2 Announce Type: replace Abstract: The subcellular localization of RNAs, including long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), microRNAs (miRNAs) and other smaller RNAs, p

local-aiarxiv-cs-cv

A Concept-informed Interpretable Artificial Intelligence Framework for Breast Ultrasound Diagnosis

arXiv:2610.16128v1 Announce Type: new Abstract: Most existing artificial intelligence systems for breast ultrasound rely primarily on image-driven prediction, with limited incorporation of the knowled

safetyarxiv-cs-cv

A Controlled Evaluation of Curvature Inspired Scalar Feature Scaling for Domain Generalization

arXiv:2610.18227v1 Announce Type: cross Abstract: Domain-specific curvature is an appealing idea for domain generalization (DG), but curvature learning can denote substantially different computations.

Local Ai

A Decade of PhotoMappers: A Longitudinal Study of Crowdsourced Disaster Photos Geolocalization with Vision-Language Models and Geospatial Reasoning

arXiv:2610.15403v1 Announce Type: cross Abstract: Crowdsourced disaster imagery provides timely, ground-level observations when conventional disaster mapping is delayed or incomplete, yet its geograph

local-aiarxiv-cs-cv

Local Ai

A Dependency-Aware Multi-GPU Training Framework for Temporal Graph Neural Networks

arXiv:2610.15730v1 Announce Type: new Abstract: Temporal graph neural networks (TGNNs) achieve superior performance in many dynamic graph learning tasks. These models use node state vectors (i.e., mem

local-aiarxiv-cs-lg

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

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

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

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

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

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