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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

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Optimal Transport Dropout for Structured Predictive Uncertainty

DGX agent

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

29 Sept 2026

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

Agents

Oracle expands AI agent features with Fusion Claw

Oracle Corp. today is introducing an agentic software runtime that lets its Fusion applications carry out complex business tasks, from reconciling accounting entries to revising staffing plans when co

agentssiliconangle

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

Ornith-1.5 DFlash

Ornith-1.5-9B-DFlash pairs the Ornith-1.5-9B model with a DFlash draft model for speculative decoding. https://huggingface.co/ornith-ai/Ornith-1.5-9B-DFlash Ornith-1.5-397B-DFlash pairs the Ornith-1.5

local-air-localllama

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

Hardware

Our Secure Intelligence Institute works with researchers at Stanford, CMU, Duke, Columbia, Ohio State, and UVA. We’re also working with NVID…

Our Secure Intelligence Institute works with researchers at Stanford, CMU, Duke, Columbia, Ohio State, and UVA. We’re also working with NVIDIA and the Open Secure AI Alliance, and sharing tools and fi

hardwareperplexity--x

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

Applications

PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory

arXiv:2609.31716v1 Announce Type: new Abstract: Persistent semantic occupancy mapping is essential for embodied scene understanding. However, perspective-based systems provide limited spatial coverage

applicationsarxiv-cs-cv

Parameter-Efficient 3D Segmentation of Liver and Liver tumors: Depthwise factorization Scales Better Than Dense Convolution with Spatial Dimensionality

arXiv:2609.33077v1 Announce Type: new Abstract: Three-dimensional dense convolutional networks are the strongest performers on volumetric medical image segmentation, but their parameter counts scale p

PARSEE-VAD: Efficient Training-Free Online Video Anomaly Detection via Proposition-Aware Reasoning and Streaming Evidence Escalation

arXiv:2609.33236v1 Announce Type: new Abstract: Training-free online video anomaly detection (VAD) with frozen multimodal language models faces two coupled challenges: extracting reliable current-wind

safetyarxiv-cs-cv

Patch Rebirth: Toward Fast and Transferable Model Inversion of Vision Transformers

arXiv:2509.23235v2 Announce Type: replace Abstract: Model inversion is a widely adopted technique in data-free learning that reconstructs synthetic inputs from a pretrained model through iterative opt

Agents

Path Planning with Motion Primitives in Dynamic Environments: SIPP on Lattices

arXiv:2609.31803v1 Announce Type: new Abstract: Autonomous navigation in dynamic environments is a critical challenge, particularly when spaces are shared with other mobile agents whose future traject

agentsarxiv-cs-ro

Patient-level validation of a foundation-model pipeline for pediatric lung sounds: physician-annotated adventitious events are recognized, disease groups are not reliably predicted

arXiv:2603.15688v2 Announce Type: replace-cross Abstract: Background: Lung-sound classifiers are usually evaluated on recording- or event-level splits, although each child contributes many recordings.

Pay for Hints, Not Answers: LLM Shepherding for Cost-Efficient Inference

arXiv:2601.22132v2 Announce Type: replace Abstract: Large Language Models (LLMs) deliver state-of-the-art performance on complex reasoning tasks, but their inference costs limit deployment at scale. S

PDMD: Projected Distribution Matching Distillation for Video Diffusion Models

arXiv:2609.35768v1 Announce Type: new Abstract: Modern video diffusion models require tens of denoising evaluations over long spatiotemporal token sequences. Distribution Matching Distillation (DMD) r

PEEL-DDPM: Physics-Enabled Evidential Learning for the Denoising Diffusion Probabilistic Model

arXiv:2609.31742v1 Announce Type: new Abstract: Normal-inverse-gamma (NIG) regression is not identifiable from its marginal Student-t likelihood: three combinations of four NIG parameters are determin

Perceptual Quality Loss or Loss of Perceptual Quality?

arXiv:2609.35054v1 Announce Type: cross Abstract: Contemporary deep speech enhancement (SE) models are often trained with specific auxiliary terms in the loss function as a way to improve their perfor

Tutorials

Period Segmentation in Transition Network Analysis: A Topological Data Analysis Approach

arXiv:2609.32094v1 Announce Type: cross Abstract: Temporal dynamics in learning behavior can be revealed through period segmentation in Transition Network Analysis (TNA). Cristea et al. demonstrated t

tutorialsarxiv-cs-lg

Permutation-Equivariant Flow Matching for Alignment-Free Neural Weight Generation

arXiv:2609.32833v1 Announce Type: new Abstract: A trained neural network can be represented by a parameter vector in high dimensions. Learning distributions over these vectors enables the generation o

Agents

Persistent Partners Raise Prices Among Learning Agents

arXiv:2609.35402v1 Announce Type: new Abstract: When pricing agents meet repeatedly on a platform, the platform decides who faces whom. We ask whether that choice moves the prices the agents learn, an

agentsarxiv-cs-lg

Perturb-and-Solve: Efficient Learned-Operator Conditioning for Latent Diffusion Inverse Problems

arXiv:2609.33171v1 Announce Type: cross Abstract: Latent diffusion models serve as powerful priors for solving inverse problems in image restoration, such as deblurring, inpainting, and super-resoluti

local-aiarxiv-cs-cv

PEST: Parameter Efficient Steering of Blackbox VLMs via Agentic Few-shot Alignment for Hateful Meme Moderation

arXiv:2601.04692v2 Announce Type: replace-cross Abstract: In this work, we examine hateful memes from three complementary angles - how to detect them, how to explain their content and how to intervene

PF-RL: Progress Field Reinforcement Learning via Goal-Conditioned Value Geometry for Vision-Language-Action Models

arXiv:2609.32634v1 Announce Type: new Abstract: Reinforcement Fine-Tuning~(RFT) has emerged as a promising paradigm for improving Vision-Language-Action~(VLA) policies, yet sparse task-level outcomes

safetyarxiv-cs-ro

PGL-3D: Towards Progressive Geometric Learning for 3D Visual Query Localization

arXiv:2609.33558v1 Announce Type: new Abstract: 3D Visual Query Localization (3DVQL) retrieves the latest contiguous occurrence of a queried object in an RGB--point-cloud sequence and predicts a 9-DoF

Phase Space Attention:A Hairer Lift Circumvents the Single-Layer Induction Obstruction

arXiv:2609.32319v1 Announce Type: new Abstract: We circumvent the Sanford-Hsu-Telgarsky (SHT) single-layer induction obstruction within a linear, one-step, causal, bilinear, symplectically consistent

Phenomenon-Graph JEPA: Label-Efficient Representation Learning for Contactless Cardiorespiratory Sensing

arXiv:2609.32928v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar and RGB-D cameras can record cardiac and respiratory waveforms continuously and without contact, but labeled recordings r

PHIRL: Aligning Learned Rewards with Task Progress for Inverse Reinforcement Learning

arXiv:2609.31855v1 Announce Type: new Abstract: Human demonstrations provide dense policy-level information but sometimes lack local precision. Human feedback presents accurate local critiques, but of

local-aiarxiv-cs-ro