Search: “papers”

Application of sequence learning for predicting radiation damage of the CMS electromagnetic calorimeter

arXiv:2610.04058v1 Announce Type: cross Abstract: In this paper we use machine learning methods to predict radiation damage in the lead tungstate crystals of the CMS electromagnetic calorimeter at the

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Safety

Barrier-Shaped Recurrent Reinforcement Learning for Autonomous Landing on a Heaving Ship Deck

DGX agent

arXiv:2610.03924v1 Announce Type: cross Abstract: This paper addresses autonomous landing of unmanned aerial vehicle (UAV) rotorcrafts on a heaving ship deck using a recurrent policy trained via asymm

safetyarxiv-cs-ro

6 Oct 2026

Base Models Can Reason By Taking a Cue From Training Data

arXiv:2610.06851v1 Announce Type: new Abstract: In this paper, we study how training data creates associations between the tokens at the start of a base model's response and the reasoning behavior tha

Billion-Scale Thumbnail Optimization for Uncurated Short-Form Videos via Multi-Armed Bandits

arXiv:2610.04931v1 Announce Type: new Abstract: This paper introduces a real-time thumbnail optimization system deployed at a global O(B) scale on a major short-form video platform. Unlike traditional

Boosting Transferable Adversarial Attacks against Deep Reinforcement Learning

arXiv:2610.06083v1 Announce Type: new Abstract: Most adversarial attacks on deep reinforcement learning (DRL) assume white-box access to the victim policy, which rarely holds in practice. This paper s

Agents

Building A Multi-Sensor Platform For Autonomous Driving Research: Challenges and Lessons Learned

arXiv:2610.05604v1 Announce Type: new Abstract: This paper reports on the challenges encountered and lessons learned during the development and deployment of a flexible multi-sensor platform for auton

agentsarxiv-cs-ro

Compact set-valued deep ensembling in multi-class classification

arXiv:2610.05332v1 Announce Type: new Abstract: This paper tackles visible challenges in deep ensemble learning, where deep neural networks serve as ensemble members: training and storage burdens, and

Distributed Cascade Force Control of Soft-Tactile-Based Multi-robot System for Object Transportation

arXiv:2610.04775v1 Announce Type: new Abstract: In this paper, we present a distributed cascade force control system (DCFC) for multiple robots with the aim of pushing a rigid object towards a desired

Do VLAs Understand and Adapt to the Objects They Handle, or Simply Replay Learned Behaviors?

arXiv:2610.06078v1 Announce Type: new Abstract: This paper asks whether VLA generalization is grounded in a global understanding of objects' physical properties that enables policies to adapt their mo

safetyarxiv-cs-ro

Emergency Obstacle Avoidance Maneuvers in Differential-Drive Mobile Robots

arXiv:2610.05607v1 Announce Type: new Abstract: Emergency obstacle avoidance requires a mobile robot to brake or change its heading within the available distance. This paper investigates the dependenc

Evolutionary feature selection for spiking neural network pattern classifiers

arXiv:2604.26654v1 Announce Type: cross Abstract: This paper presents an application of the biologically realistic JASTAP neural network model to classification tasks. The JASTAP neural network model

Finite-Sample Distribution Theory and Efficient Large-Scale Inference for Online Quantile Regression

arXiv:2610.05869v1 Announce Type: cross Abstract: This paper studies online quantile regression for large-scale and streaming data using Stochastic SubGradient Descent (SSGD) with constant learning ra

Flip-Flop Consistency: Unsupervised Training for Robustness to Prompt Perturbations in LLMs

arXiv:2510.14242v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) often produce inconsistent answers when faced with different phrasings of the same prompt. In this paper, we prop

Human-in-the-Loop Neuro-Symbolic Drift Anticipation for Reliable Visual SLAM

arXiv:2610.05757v1 Announce Type: new Abstract: This paper introduces Hybrid DeepSEE (HDS), a Human-in-the-Loop (HITL) neuro-symbolic framework for proactive drift anticipation in Visual SLAM (V-SLAM)

Kolmogorov-Arnold Networks for Personal Context Recognition on ExtraSensory

arXiv:2610.05250v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) have attracted increasing attention in recent years, with applications across a wide range of AI tasks. In this paper

Large Stepsizes Federated Learning on Logistic Regression with Linearly Separable Data: The Case of Heterogeneous Devices

arXiv:2610.05915v1 Announce Type: new Abstract: This paper revisits the distributed learning problem for training a multinomial logistic regression model with the Federated Averaging (exttt{FedAvg}) a

Applications

MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation

arXiv:2503.09950v2 Announce Type: replace Abstract: In this paper, we address the problem of human trajectory forecasting, which aims to predict the inherently multi-modal future movements of humans b

applicationsarxiv-cs-cv

Local Ai

Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

arXiv:2610.04545v1 Announce Type: cross Abstract: This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributi

local-aiarxiv-cs-ro

On architectural choices for interpretability and thermodynamic consistency in Physically Recurrent Neural Networks in the low-data regime

arXiv:2610.04067v1 Announce Type: new Abstract: In this paper, we unravel the effect of different decoder architectures on the interpretability of the latent space of the Physically Recurrent Neural N

PatternDex: Learning Interaction Patterns to Guide Reinforcement Learning of Bimanual Dexterous Manipulation of Articulated Objects

arXiv:2610.04765v1 Announce Type: new Abstract: In this paper, we develop a method that enables bimanual dexterous hands to manipulate articulated objects with a high success rate without suffering fr

safetyarxiv-cs-ro

Local Ai

Personal VAD: Speaker-Conditioned Voice Activity Detection

arXiv:1908.04284v5 Announce Type: replace-cross Abstract: In this paper, we propose 'personal VAD', a system to detect the voice activity of a target speaker at the frame level. This system is useful

local-aiarxiv-cs-lg

Prompt Dominance and Asymmetric Verifier Costs: Empirical Ablations of GRPO at 1B Scale on GSM8K

arXiv:2610.04928v1 Announce Type: new Abstract: This paper studies GRPO at 1B scale from both directions: what estimator choices do to the learning signal, and what a degraded reward signal does to wh

Tutorials

Questioning the Questions: Sustaining Self-Evolution in Reasoning Models

arXiv:2610.04299v1 Announce Type: new Abstract: Self-evolving reasoning models learn from their own generated questions, yet repeated self-training can lead to performance collapse. In this paper, we

tutorialsarxiv-cs-lg

RAC: Rectified Flow Auto Coder

model-releasesarxiv-cs-cv

arXiv:2603.05925v2 Announce Type: replace Abstract: In this paper, we propose a Rectified Flow Auto Coder (RAC) inspired by Rectified Flow to replace the traditional VAE: 1. It achieves multi-step dec

Real-Time Conformal-Seeded Hybrid Inverse Kinematics for Offset Redundant Manipulators

arXiv:2610.04266v1 Announce Type: new Abstract: This paper presents a conformal-seeded hybrid strategy for solving inverse kinematics of offset, redundant 7-DoF robot arms of the humanoid class. Analy

Screw Geometry Meets Bandits: Incremental Acquisition of Demonstrations to Generate Manipulation Plans

arXiv:2410.18275v2 Announce Type: replace Abstract: In this paper, we study the problem of methodically obtaining a sufficient set of kinesthetic demonstrations, one at a time, such that a robot can b

Local Ai

Shared Geometry Is Not Shared Physics: A Layerwise Test of the Platonic Representation Hypothesis in Astronomy

arXiv:2610.04130v1 Announce Type: cross Abstract: In this paper we investigate whether geometrically aligned astronomical representations are also scientifically interchangeable. We analyze every laye

local-aiarxiv-cs-lg

Sparse Calibration-Based Personalization of Kernel-Based Gait Phase and Speed Estimation Using Wearable IMUs

arXiv:2610.03931v1 Announce Type: new Abstract: This paper presents sparse calibration-based personalization for kernel-based gait phase and walking speed co-estimation from wearable inertial measurem

Applications

Structural Foundations of Nonlinear Systems with Unknown Inputs: The UID-Induced Normal Form and Minimal-Sensing Structure-from-Motion

arXiv:2610.05939v1 Announce Type: cross Abstract: This paper establishes the first general structural solution to the problem of state estimation for nonlinear systems driven by unknown inputs. Buildi

applicationsarxiv-cs-cv

Agents

Synergizing Drone Delivery Order Pooling and Road Network Monitoring through Monitoring-Task Orderization

arXiv:2610.05270v1 Announce Type: cross Abstract: This paper investigates the real-time dispatch of a shared drone fleet for on-demand food delivery and urban road network monitoring. We consider a co

agentsarxiv-cs-lg

Textual Echo Cancellation

arXiv:2008.06006v5 Announce Type: replace-cross Abstract: In this paper, we propose Textual Echo Cancellation (TEC) - a framework for cancelling the text-to-speech (TTS) playback echo from overlapping

Vision-enabled detection of safety helmet compliance in construction zones

arXiv:2610.05756v1 Announce Type: new Abstract: In the rapidly evolving field of construction management, worker safety remains a top priority. This paper introduces an innovative vision-based system

safetyarxiv-cs-cv

Asterism: Exploring and Synthesizing Scattered Observations into Literature-Grounded Hypotheses and Theories

arXiv:2610.02673v1 Announce Type: cross Abstract: A theory draws many independent observations into one framework with novel hypotheses. A researcher building such a theory must synthesize observation

researcharxiv-cs-cl

Error Propagation in Dynamic Programming: From Stochastic Control to American Option Pricing

arXiv:2509.20239v2 Announce Type: replace-cross Abstract: This paper investigates theoretical and methodological foundations for stochastic optimal control (SOC) in discrete time. We start formulating

From Expression to Reaction: Role-aware Visual Transfer and Stimulus-guided Reasoning for Interlocutor Emotion Recognition

arXiv:2610.03016v1 Announce Type: cross Abstract: In this paper, we propose a Role-aware Stimulus-guided (RASG) framework for interlocutor emotion recognition, which predicts listener emotions from li

researcharxiv-cs-cv

Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis

arXiv:2610.03717v1 Announce Type: cross Abstract: This paper examines the role of Novel View Synthesis (NVS) in geometric representation learning. In principle, NVS should reason about 3D scene struct

researcharxiv-cs-ai

Near-Optimal Convex Optimization with Lazy Second-Order Oracles

arXiv:2610.03222v1 Announce Type: cross Abstract: This paper studies the complexity of convex optimization using lazy second-order oracles (Doikov, Chayti, and Jaggi, ICML 2023), where an algorithm qu

Agents

Source Preference in the Wild: How LLM Agents Favor Items by Source, and How to Reduce It

arXiv:2610.03195v1 Announce Type: new Abstract: As LLM agents decide on users' behalf which product to buy, which hotel to book, or which paper to cite, a preference for items from certain sources (th

agentsarxiv-cs-cl

TRAC: Trajectory-aware Reuse and Adaptive Correction for Efficient Autoregressive Video Generation

arXiv:2610.02779v1 Announce Type: new Abstract: In this paper, we present trajectory-aware reuse and adaptive correction (TRAC), a training-free framework for efficient autoregressive (AR) video gener

researcharxiv-cs-cv

Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems

arXiv:2307.07113v2 Announce Type: replace-cross Abstract: In this paper, we consider the decentralized, stochastic nonconvex strongly-concave (NCSC) minimax problem with nonsmooth regularization terms

AdaptManip: Learning Adaptive Whole-Body Object Lifting and Delivery with Online Recurrent State Estimation

arXiv:2602.14363v2 Announce Type: replace-cross Abstract: This paper presents Adaptive Whole-body Loco-Manipulation, AdaptManip, a fully autonomous framework for humanoid robots to perform integrated

Admissibility-Preserving Control for Multi-Input Systems with Joint Capacity Constraints

arXiv:2610.00533v1 Announce Type: cross Abstract: This paper addresses the control of multi-input strict-feedback nonlinear systems subject to a joint capacity constraint, in which the admissible inpu

An ontology for cross-sectoral crisis management: core and public health modules

model-releasesarxiv-cs-ai

arXiv:2610.01326v1 Announce Type: new Abstract: This paper presents the European Crisis Management Ontology (ECMO), a modular OWL-based ontology intended as a cross-sectoral reference for disaster ris

Better Convergence Guarantees for Sign-Based Momentum Methods

arXiv:2507.12091v2 Announce Type: replace-cross Abstract: This paper presents an improved analysis for sign-based methods with momentum updates. Traditional sign-based methods obtain a convergence rat

Beyond Affine Transformations: A Soft Dominance Layer for Coordinate-Wise Neural Computation

model-releasesarxiv-cs-ai

arXiv:2610.00563v1 Announce Type: cross Abstract: This paper presents a preliminary study of an alternative to the affine transformation underlying conventional neural-network layers. In the proposed

Beyond Supra-Competitive Outcomes: Collusive Behaviour in Deep Reinforcement Learning for Optimal Execution Games

model-releasesarxiv-cs-ai

arXiv:2610.00619v1 Announce Type: cross Abstract: In this paper, we extend earlier findings of supra-competitive outcomes in optimal-execution games by identifying a learned punitive mechanism that de

Classical Hardness of Learning Functions of Hamiltonians

arXiv:2610.01141v1 Announce Type: cross Abstract: Morohoshi, Nakayama, Manabe, and Mitarai proposed a physically motivated quantum machine learning problem in which the goal is to predict quantities o

Decentralized Safe Path Following for Multiple Quadrotors on Intersecting Paths with Theoretical Guarantees

arXiv:2610.00208v1 Announce Type: cross Abstract: This paper studies decentralized safe path following for multiple quadrotors on intersecting paths, where safety requires both collision avoidance and

safetyarxiv-cs-ro