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Patient-Reported Survey Data Improve Prediction of Opioid Use Disorder

arXiv:2609.12224v1 Announce Type: new Abstract: Electronic health records (EHRs) may incompletely capture patient-reported factors associated with opioid use disorder (OUD). We evaluated whether surve

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PEARL: Structural Privacy-Utility Control in Human-Centric CPS via Personalized Early-Exit Deep Reinforcement Learning

DGX agent

arXiv:2403.05864v3 Announce Type: replace Abstract: In human-centric Cyber-Physical Systems (CPS), personalized Deep Reinforcement Learning (DRL) agents must share fine-grained control actions with cl

researcharxiv-cs-lg

14 Sept 2026

Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence

arXiv:2609.12036v1 Announce Type: new Abstract: In this technical report, we propose Pelican-Sim 1.0, a general world model simulator for embodied intelligence that predicts future observations from v

safetyarxiv-cs-ro

Hardware

Performance, Efficiency and Collapse -- Advantages and Challenges in Offline Post-training of Code LLMs

arXiv:2609.11956v1 Announce Type: new Abstract: Post-training with reinforcement learning (RL) is a critical phase in the development of code-generating large language models (LLMs), as it ensures adh

hardwarearxiv-cs-lg

Physical-State-Guided Diffusion Sampling for Full-Waveform Inversion

arXiv:2609.12899v1 Announce Type: new Abstract: Full waveform inversion (FWI) estimates subsurface velocity from seismic recordings, but its ill-posedness and nonlinearity make accurate reconstruction

Physics as the label for measuring and correcting materials reasoning in multimodal models

arXiv:2609.12181v1 Announce Type: new Abstract: Vision-language and language models increasingly interpret materials data, yet benchmarks report that they hallucinate invalid properties and violate ph

Physics-Aware Video Generation via Agentic Planning and Graph-Guided Optimization

arXiv:2609.13006v1 Announce Type: new Abstract: Video diffusion models (VDMs) have demonstrated remarkable capabilities in synthesizing high-fidelity, photorealistic video content. However, they funda

agentsarxiv-cs-cv

Hardware

Physics-enriched neural solvers for transient ice-flow simulation

arXiv:2609.12900v1 Announce Type: cross Abstract: Transient glacier simulations with higher-order ice flow require the repeated solution of a nonlinear problem as the geometry evolves. In the online m

hardwarearxiv-cs-lg

Physics-Guided Synthetic High-Frequency Ultrasound Generation for Skin Layer Segmentation

arXiv:2609.12735v1 Announce Type: cross Abstract: High-frequency ultrasound (HFUS) enables noninvasive visualization of superficial skin structures, but automated skin-layer analysis is limited by the

Physics-Informed Conformal Prediction: Embedding PDE Consistency into Distribution-Free Uncertainty Quantification for Neural Operators

arXiv:2609.11935v1 Announce Type: new Abstract: Neural operators such as the Fourier Neural Operator (FNO) achieve remarkable accuracy in approximating solutions to partial differential equations (PDE

PhysioAI: Clinical Knowledge-Guided Semantic Supervision for Skeleton-Based Physiotherapy Action Recognition

arXiv:2609.12491v1 Announce Type: new Abstract: Skeleton-based action recognition can support automated tracking of physiotherapy exercises, particularly in remote rehabilitation settings where contin

Applications

PinDCO: Whole-Page Aware Dynamic Creative Optimization at Scale

arXiv:2609.11943v1 Announce Type: cross Abstract: Recent advances in generative AI have substantially accelerated the creation of high-quality ad creatives, dramatically expanding the number of candid

applicationsarxiv-cs-lg

Pixel Decodability Is Not a Compression Signal: Causally Evaluating Importance Proxies for Visual KV-Cache Eviction

arXiv:2609.13012v1 Announce Type: new Abstract: Vision-language models retain a substantial amount of pixel-decodable visual content in their visual key-value cache. We show, in our setting, that this

PLSP (Pre-hoc Liminal Space Profiling): OOD Prediction over Detection -- An Anticipatory Approach for Machine Learning Model Reliability

arXiv:2609.12225v1 Announce Type: cross Abstract: Out-of-Distribution (OOD) data poses a significant threat to machine learning models, often leading to model failure during deployment. All existing O

Pneumatic neurons for soft robots enable inflate-and-fire networks for rhythmic motion

arXiv:2609.12258v1 Announce Type: new Abstract: Animals coordinate their movements through distributed neural circuits, but soft robots still typically depend on external, centralized electronics for

researcharxiv-cs-ro

Poisson-Corrector Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

arXiv:2609.12594v1 Announce Type: new Abstract: We study the classical Moreau--Yosida unadjusted Langevin algorithm (MYULA) for pi(,d x)propto e^{-f(x)-g(x)},d x, where fin C^2(R^d) is m-strongly conv

safetyarxiv-cs-lg

Population-level measures of perceived food access reveal barriers beyond geographic proximity

arXiv:2609.12132v1 Announce Type: new Abstract: Food access is multidimensional, but population-level measurement still relies heavily on geography because perceived dimensions of access are difficult

Pre-Trained Low-Rank Tensor Decomposition for Multi-Dimensional Image Recovery

arXiv:2609.12843v1 Announce Type: new Abstract: Recently, tensor decompositions are prevalent for multi-dimensional image representation, which learn the instance-specific structure of each image from

tutorialsarxiv-cs-cv

Predicting Collision Cross Sections with GRACE: Geometric Residual Adduct Conditioning via Early-fusion

arXiv:2609.12223v1 Announce Type: new Abstract: Collision cross section (CCS), derived from ion mobility mass spectrometry, is a common descriptor for molecular annotation. Prediction is challenging f

Prism-SQA: An Interpretable and Adaptable Neural Framework for Surface Electromyography Quality Assessment

arXiv:2609.12724v1 Announce Type: cross Abstract: sEMG is vulnerable to various contaminants that distort signal morphology and spectral content. Accurate signal quality assessment (SQA) is essential

PRISMA-LLM: An Empirical Reporting Framework for AI-Assisted Systematic Reviews

arXiv:2609.11559v1 Announce Type: cross Abstract: Large language models (LLMs) and AI-enabled software increasingly participate in systematic-review decisions, yet the information needed to audit thes

ProactiveBench: Can Streaming Video Models Really Interact Like Humans?

arXiv:2609.12658v1 Announce Type: new Abstract: Streaming video understanding requires models to process continuous multimodal input while maintaining temporal context. Existing evaluations are predom

ProClosure: Hierarchical Room-Object Assignment using Progressive Boundary Closure from Monocular Video

arXiv:2609.12614v1 Announce Type: new Abstract: A 3D scene graph groups objects into rooms. When a robot is asked to fetch an object from the kitchen, that grouping is what tells it where to look. An

researcharxiv-cs-ro

Protect Your Score: Contact Tracing With Differential Privacy Guarantees

arXiv:2312.11581v3 Announce Type: replace-cross Abstract: The pandemic in 2020 and 2021 had enormous economic and societal consequences, and studies show that contact tracing algorithms can be key in

agentsarxiv-cs-lg

QTrans: A Quantum Transformer for Sentiment Classification

arXiv:2609.12011v1 Announce Type: new Abstract: In small-scale binary sentiment classification scenarios, factors such as negation, contrastive shifts, and cross-word dependencies lead to the non-line

Quality-Constrained Routing over a Fixed Pool of Quantized Mixture-of-Experts Instances

model-releasesarxiv-cs-lg

arXiv:2609.12550v1 Announce Type: new Abstract: Quantized Mixture-of-Experts (MoE) services can hold several pre-materialized instances of one base model, but quantization damage varies sharply across

Quantifying Consonant Contributions to Word Intelligibility via Acoustic Masking

arXiv:2609.12122v1 Announce Type: new Abstract: Consonants contribute unequally to whether a word is understood. Given the limited time available for therapy, ranking consonants by contribution to int

Quantifying Spectral Differences in Vehicle Between Production Autonomous and Human-Driven Vehicles Across Driving Scenarios

arXiv:2609.12609v1 Announce Type: new Abstract: Differences in vehicle kinematic characteristics between production autonomous vehicles (PAVs) and human-driven vehicles (HVs) have been limitedly inves

agentsarxiv-cs-ro

Quantifying the Value of Privileged Information Using a PAC-Bayesian Approach

arXiv:2609.12891v1 Announce Type: new Abstract: In practice, various learning scenarios provide access to auxiliary features exclusively during training. Incorporating such data to enhance model perfo

Quantile-based Loss Filtering for Outlier-Robust Stochastic Gradient Descent

arXiv:2609.13040v1 Announce Type: new Abstract: We study loss-based filtering for finite-sum optimization with a subset of corrupted component functions whose gradients may be highly unreliable. Motiv

QuPAINT: Physics-Aware Multimodal Reasoning for Quantum Material Characterization

arXiv:2609.12202v1 Announce Type: new Abstract: Characterizing two-dimensional (2D) quantum materials by optical microscopy requires localizing exfoliated flakes and determining their layer thickness

R^2M: Real-Aware Residual Model Merging for Robust and Generalizable Deepfake Detection

arXiv:2509.24367v2 Announce Type: replace Abstract: Deepfake generators evolve rapidly, making exhaustive data collection and repeated retraining impractical. Unlike generic multi-task settings, deepf

R2VC: Modular Fact-Checking with Retrieval, Verification, and Confidence Calibration

arXiv:2609.11955v1 Announce Type: new Abstract: Large language models are increasingly used for automated fact checking, but end-to-end prompting often entangles evidence retrieval, reasoning, and unc

Applications

RA-SOD: Reliability-Aware RGB-T Salient Object Detection under Modality Degradation

arXiv:2609.12622v1 Announce Type: new Abstract: RGB-Thermal (RGB-T) salient object detection leverages complementary cues from visible and thermal modalities to improve robustness in challenging envir

applicationsarxiv-cs-cv

Rank-Efficient LoRA via Joint Tangent-Space Optimization under Isotropic Curvature

model-releasesarxiv-cs-lg

arXiv:2609.12123v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is an effective approach for adapting large pretrained models by learning low-rank weight updates. In practice, the LoRA rank

READ: Learning Risk-Informed Fields for End-to-End Autonomous Driving

arXiv:2609.12371v1 Announce Type: new Abstract: Autonomous driving requires more than recognizing what is present in a scene: a planner must determine how road structure, surrounding agents, and their

safetyarxiv-cs-ro

Receiver-Surface Hit Patterns via Legendre Approximation for Molecular Signal Detection

arXiv:2609.12089v1 Announce Type: cross Abstract: Detecting whether a transmitter is actively communicating with a receiver is a fundamental problem in molecular communications. A spherical receiver m

Recurrent Dynamic Range Extension

arXiv:2609.13135v1 Announce Type: cross Abstract: We present an approach to progressively extend the highlights of an image. Instead of reconstructing the full dynamic range of a complex scene directl

tutorialsarxiv-cs-cv

Reinforcement Learning for Syndrome Extraction

arXiv:2609.12020v1 Announce Type: new Abstract: A key subtask of quantum error correction is to extract a syndrome that, if nontrivial, signals an error. The number of possible ways to extract a syndr

Reinforcement Learning over Patient Trajectories for Clinical Reasoning in EHR Foundation Models

arXiv:2609.12277v1 Announce Type: new Abstract: Electronic health record (EHR) foundation models trained on longitudinal patient trajectories have demonstrated strong performance across diverse clinic

safetyarxiv-cs-lg

RelateAnything: Real-Time Open-Vocabulary Relation Prediction From Any Inputs

arXiv:2609.12552v1 Announce Type: new Abstract: Open-vocabulary detection accepts any class list at inference, and promptable segmentation returns regions without class names: the taxonomy has left th

Repair Before Reinforce: Context-Augmented Knowledge Graph Reasoning for Multi-Hop Question Answering

arXiv:2609.12230v1 Announce Type: new Abstract: Question-answering often requires reasoning across multiple connected facts rather than retrieving a single isolated relation. Knowledge graphs (KGs) pr

tutorialsarxiv-cs-cl

Representation-based Masked Diffusion Model

arXiv:2609.12382v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) have emerged as a compelling paradigm for language modeling, offering the capability for efficient parallel text generati

tutorialsarxiv-cs-cl

Residual Vector-based Reconstruction as Long-Context Recall Regardless of Context Window Size

model-releasesarxiv-cs-cl

arXiv:2609.12686v1 Announce Type: cross Abstract: Large language models (LLMs) process long contexts, including long documents and lengthy conversations, but face token-level memory usage that increas

Retriever: Composing the Perception-Reasoning-Action Loop for Long-Horizon Manipulation

arXiv:2607.17213v2 Announce Type: replace Abstract: Building long-horizon robot agents requires composing closed-loop pipelines -- perception, belief update, planning, and control -- whose components

agentsarxiv-cs-ro

Revisiting Multi-Object Tracking Baselines: Hyperparameter Optimization with Multi-Fidelity Greedy Coordinate Search

arXiv:2609.12261v1 Announce Type: new Abstract: Multi-object tracking (MOT) is dominated by the tracking-by-detection paradigm, whose methods typically rely on a small set of hyperparameters that are

RiPPLE: Cross-Space Performance Prediction from Early Training for Neural Architecture Search

arXiv:2609.12418v1 Announce Type: cross Abstract: Neural architecture search (NAS) evaluates candidate networks, but fully training enough architectures to rank an entire space is expensive. Zero-cost

Robust Policy Optimization via Adversarial Importance Sampling

arXiv:2609.13044v1 Announce Type: new Abstract: Significant progress has been made in safeguarding deep reinforcement learning (DRL) policies against input perturbations. Developing robust DRL involve

safetyarxiv-cs-lg