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On the Numerical Reliability of Differentiable Physics-Based Optimization for Robotic Material Manipulation

arXiv:2609.34666v1 Announce Type: cross Abstract: Differentiable physics is increasingly used in robotic material manipulation for system identification, trajectory or skill optimization, demonstratio

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On the O(frac{sqrt{d}}{K^{1/4}}) Convergence Rate of AdamW Measured by ell_1 Norm

DGX agent

arXiv:2505.11840v4 Announce Type: replace Abstract: As the default optimizer for training large language models, AdamW has achieved remarkable success in deep learning. However, its convergence behavi

applicationsarxiv-cs-lg

29 Sept 2026

On the Pitfalls of Verbalized Confidence Priors for Calibrating Large Reasoning Models

arXiv:2609.32470v1 Announce Type: new Abstract: Large reasoning models (LRMs) often suffer from overconfidence when expressing their uncertainty. Confidence-aware reinforcement learning (RL) offers a

Tutorials

On the Relation Between Interval Regret and Dynamic Regret

arXiv:2609.34423v1 Announce Type: new Abstract: Non-stationary online learning has attracted much attention in recent years, as static regret is insufficient to guide algorithm design in changing envi

tutorialsarxiv-cs-lg

On the Two Faces of Adam in Separable Linear Classification

arXiv:2609.33904v1 Announce Type: new Abstract: We consider the behavior of deterministic, full-batch, bias-corrected Adam in separable linear classification with softmax parametrization under log-los

One Attack to Fool Them All: Highly Transferable Black-Box Adversarial Attacks on Frontier MLLMs

arXiv:2609.33833v1 Announce Type: new Abstract: Adversarial attacks have long posed a fundamental threat to machine learning systems. As multimodal large language models (MLLMs) rapidly evolve and bec

One Evaluation, Any Operating Point: Hypernetwork-Amortized MeanFlow for 3D MRI Reconstruction

arXiv:2609.31655v1 Announce Type: new Abstract: Generative priors reconstruct accelerated 3D MRI well but pay heavily at deployment: tens of network evaluations per volume, and protocol-specific hyper

One Perception, All Maneuvers: Directional Traffic Signal Understanding for Maneuver-Level Signal Intent Prediction

arXiv:2609.32316v1 Announce Type: new Abstract: Traffic lights are a key regulatory signal for autonomous driving at urban intersections, yet existing traffic signal perception is still predominantly

One Proposal for Every Margin: Zero-Shot Amortized Sequential Importance Sampling for Binary Matrices

arXiv:2609.35514v1 Announce Type: new Abstract: In ecology, psychometrics, and the analysis of social and financial networks, binary matrices are often analyzed conditional on their observed row and c

One Rollout Is All You Get: Fully Test-Time Adaptation for GUI Agents

arXiv:2609.34321v1 Announce Type: new Abstract: GUI agents are deployed with frozen weights and discard everything they experience on the job. Existing ways to update an agent's weights assume somethi

agentsarxiv-cs-lg

One Sensor, Whole Body - 3D Body Pose from a Single Consumer Earbud IMU

arXiv:2609.34978v1 Announce Type: new Abstract: Consumer earbuds already stream inertial motion data from the head, one of the most widely worn sensor locations on the body. We ask how much of the 3D

Local Ai

One Sequence, Many Decodings: CAGenMol-2 Recasts Drug Design as Masked Molecular Inference

arXiv:2609.34301v1 Announce Type: new Abstract: Drug design couples property evaluation, conditional generation, structure-based design, and local optimization, yet machine learning systems typically

local-aiarxiv-cs-lg

One-Step Generative Modeling via Unbalanced Optimal Transport

arXiv:2609.32708v1 Announce Type: cross Abstract: Drifting models enable one-step generation by amortizing distribution transport into training, but this efficiency places greater demands on the trans

One-Step Is Optimal: Unconditional Rectified Flows are Noise2Noise Denoisers, and Multi-Step Integration Provably Hurts---A Benchmark and Task-Based Detectability Study on Low-Dose CT

arXiv:2609.31670v1 Announce Type: new Abstract: Iterative and generative denoisers are increasingly used under the assumption that multi-step refinement outperforms a single regression pass. We show t

OneCanvas: 3D Scene Understanding via Panoramic Reprojection

arXiv:2606.19253v2 Announce Type: replace Abstract: Existing approaches to 3D scene understanding in Vision-Language Models (VLMs) either rely on complex, model-specific geometry encoders or large tra

OneFixer: High-Quality and Consistent One-Step Autoregressive 3DGS Refinement for Driving Scenes

arXiv:2609.32175v1 Announce Type: new Abstract: Autoregressive video diffusion is a promising render-time fixer for 3D Gaussian Splatting (3DGS) in autonomous-driving simulation, but deployment demand

safetyarxiv-cs-cv

OneSign: Unifying Sign Language Understanding Tasks with One Model

arXiv:2609.33090v1 Announce Type: cross Abstract: SLU encompasses a diverse set of tasks, including ISLR, CSLR, and SLT. Although these tasks share basic semantic and linguistic foundations, they are

Local Ai

OOD Generalization as a Bifurcation Problem

arXiv:2609.33562v1 Announce Type: new Abstract: Systematic out-of-distribution (OOD) generation remains a critical bottleneck for continuous-time generative models. While standard joint classifier-fre

local-aiarxiv-cs-lg

OpenMASC: An Open-Source Pipeline for Cross-Trajectory Metal-Aware Sampling and Correction in Accelerated MRI

arXiv:2609.32343v1 Announce Type: new Abstract: Metal implants corrupt MRI measurements throughout k-space, yet existing accelerated MRI methods assume clean data and most metal artifact reduction app

agentsarxiv-cs-cv

OpenTumorBoard: A Real-World Benchmark of Multidisciplinary Tumor Board Discussion Trajectories

arXiv:2609.32810v1 Announce Type: cross Abstract: Multidisciplinary tumor boards integrate multimodal clinical observations and longitudinal patient histories through specialist discussions, yet bench

OPERA: A Unified Omnimodal Progressive Spatio-Temporal Reasoning Agent for Referring Video Segmentation

arXiv:2609.33338v1 Announce Type: new Abstract: Referring video segmentation with heterogeneous multimodal queries---spanning text, audio, and reference images---demands both robust cross-modal unders

agentsarxiv-cs-cv

OPIS: An Input-Grounded Benchmark for Multi-Object Memory in Video World Models

arXiv:2609.35052v1 Announce Type: new Abstract: Video world models must preserve the visual state of the world over time, but existing evaluation protocols often rely on generated histories, video ref

Optimal Networks for Agentic Information Aggregation

arXiv:2609.35537v1 Announce Type: new Abstract: We study information aggregation in the networked learning model introduced by Kearns, Roth, and Ryu (SODA 2026). There is a fixed distribution over d f

agentsarxiv-cs-lg

Optimal Nonparametric Dynamic Pricing with Censored Demand and Adversarial Inventory

arXiv:2609.32949v1 Announce Type: new Abstract: We study online dynamic pricing with censored demand, where an arbitrary inventory level is revealed before pricing and may adapt to past observations,

Tutorials

Optimal Transport Dropout for Structured Predictive Uncertainty

arXiv:2609.33377v1 Announce Type: new Abstract: Deterministic neural networks and neural operators provide point predictions with no intrinsic measure of reliability. Yet, predictive uncertainty may s

tutorialsarxiv-cs-lg

Optimal transport meets speech: a tutorial review

arXiv:2609.31787v1 Announce Type: cross Abstract: Optimal Transport (OT) provides a principled framework for comparing and transforming probability distributions while preserving geometric structure.

Optimizing and Securing the Modern Watermarking Channel for Images

arXiv:2609.34744v1 Announce Type: cross Abstract: To comply with recent regulations requiring traceable generated content, modern watermarking has adopted multi-bit post-hoc watermarking schemes. Thes

Optimizing H-Graph Hybridization for Diffusion-Guided RRT

arXiv:2609.32897v1 Announce Type: new Abstract: Sampling-based motion planners guided by diffusion models produce high-quality trajectories in a single run, yet the stochastic diversity available at i

Optimizing the Phi-2 Small Language Model for Real-time Chatbot Applications Using Parameter-Efficient Fine-Tuning (PEFT) with QLoRA Quantization

arXiv:2609.33927v1 Announce Type: new Abstract: This study explores the optimization of the Phi-2 Small Language Models (SLMs) for real-time chatbot applications through Parameter-Efficient Fine-Tunin

Oracle-Efficient Online Classification with Stochastic Inputs and Adversarial Outputs

arXiv:2609.33760v1 Announce Type: new Abstract: We consider contextual binary prediction with i.i.d. contexts from an unknown distribution and adaptively chosen losses. We show that a simple Follow-th

Oracle Gaps in Reliability Coverage: Sampling Noise or Policy Specialization?

arXiv:2609.32996v1 Announce Type: new Abstract: Policies trained from the same base model can appear to solve different problems. An oracle that chooses the best policy for each problem may therefore

ORAV: Benchmarking Audio-Video Generation from Multimodal Contexts

arXiv:2609.34843v1 Announce Type: new Abstract: Audio-video generation using heterogeneous multimodal references has emerged as a new challenge, requiring both compositional control over generation an

OrientedFormer: An End-to-End Transformer-Based Oriented Object Detector in Remote Sensing Images

arXiv:2409.19648v2 Announce Type: replace Abstract: Oriented object detection in remote sensing images is a challenging task due to objects being distributed in multi-orientation. Recently, end-to-end

ORPG: Reconciling Multiple Reward Objectives through Objective-wise Policy Gradients

arXiv:2609.34985v1 Announce Type: new Abstract: Multi-reward policy optimization requires a joint update that reflects both the learning signals and the intended relationships among objectives. We int

Orthogonal Witness Control for Muon Optimization via Sigmoid Spectral Reshaping

arXiv:2609.33194v1 Announce Type: new Abstract: Matrix-valued optimizers such as Muon exploit the spectral structure of neural network updates through Newton--Schulz orthogonalization, but their near-

OSCC: Certified Observation-Safe Coupling Optimization for Gradient-Noise Control in Imperfect-Information Learning

arXiv:2609.33543v1 Announce Type: cross Abstract: Coupled rollouts can reduce the noise of counterfactual action comparisons, but two issues prevent standard common-random-number constructions from se

Local Ai

Output-aware Residual Stream Pruning for Large Language Models

arXiv:2609.35579v1 Announce Type: new Abstract: Residual stream pruning methods reduce inference cost by shrinking the model's hidden dimension, but existing approaches typically choose these dimensio

local-aiarxiv-cs-lg

Over-the-Air Federated Learning in Heterogeneous Mobile Wireless Networks

arXiv:2609.32832v1 Announce Type: new Abstract: Over-the-air computation has emerged as a scalable and efficient solution for deploying federated learning algorithms in wireless networks by exploiting

Overfitting of Spectral Gradient Descent: How Matrix Geometry shapes Generalization and Implicit Bias

arXiv:2609.32270v1 Announce Type: cross Abstract: We study the generalization of spectral gradient descent (SpecGD) in overparameterized matrix classification with corrupted labels. Each input combine

P^2O: Joint Policy and Prompt Optimization

arXiv:2603.21877v4 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) enhances Large Language Model (LLM) reasoning but is suffer from advantage collapse: when all

P2P: Cross-View Population Denoising for Unpaired Single-Cell Perturbation Response Prediction

arXiv:2609.34391v1 Announce Type: cross Abstract: AIVC (AI Virtual Cell) is a learned simulator of cellular behavior across conditions. Predicting how a cell population responds transcriptionally to a

P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration

arXiv:2609.34867v1 Announce Type: new Abstract: Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory c

PACER: Progressive Availability-Conditioned Evidence Routing for Radiology Report Generation under Incomplete Clinical Context

arXiv:2609.34487v1 Announce Type: new Abstract: Radiology report generation (RRG) increasingly incorporates heterogeneous clinical evidence, such as multi-view radiographs and previous reports, whose

PACGNet: Pyramidal Adaptive Cross-Gating Network for Multimodal Object Detection in Aerial Imagery

arXiv:2512.18291v3 Announce Type: replace Abstract: Object detection in aerial imagery is challenging because targets are often small, backgrounds are cluttered, and imaging conditions vary substantia

PalmLeaf-VQA: A Multi-Script Visual Question Answering Benchmark for Historical Palm-Leaf Manuscript Understanding Across Diverse Regions

arXiv:2609.31651v1 Announce Type: new Abstract: Historical manuscripts remain largely absent from modern vision-language benchmarks, leaving open how well multimodal large language models (MLLMs) hand

PanoFuse: Panorama-Enhanced Vision-Language-Action Learning with Decoupled Semantic-Geometric Routing

arXiv:2609.31717v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies have shown promising performance in language-conditioned robotic manipulation. However, most existing VLA systems

Panoptic Scene Program Diffusion Transformer

arXiv:2609.31780v1 Announce Type: new Abstract: Modern text-to-image models produce high-fidelity images but still struggle with compositional prompts that require instance identity, attribute ownersh

Applications

PanoVLN: Towards Effective Panoramic Vision-and-Language Navigation

arXiv:2609.34759v1 Announce Type: new Abstract: Recent vision-language models (VLMs) have advanced vision-and-language navigation (VLN), enabling models to predict navigation actions from visual obser

applicationsarxiv-cs-cv