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P-POSEMEM: Projective Semantic Memory for Consistent Language Grounding under Pose-Graph Rewrites

arXiv:2609.15475v1 Announce Type: new Abstract: A robot following language instructions needs its semantic memory to keep naming the same physical object while the SLAM pose graph underneath is optimi

researcharxiv-cs-ro

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Model Releases

PACE: Progressive Angular-to-Norm Contrastive Embedding

DGX agent

arXiv:2609.15152v1 Announce Type: cross Abstract: Multimodal embedding models encode heterogeneous inputs into a shared embedding space, enabling efficient similarity computation across modalities and

model-releasesarxiv-cs-ai

15 Sept 2026

Parameter-Efficient Adaptation of Pretrained Language Models for Time-Series Forecasting

arXiv:2609.15344v1 Announce Type: new Abstract: We study the adaptation of pretrained language models to univariate time-series forecasting through a parameter-efficient transfer learning framework, w

Parameter-Efficient Fine-Tuning of Foundation Models for Liver Tumor Segmentation in CT

arXiv:2609.14106v1 Announce Type: new Abstract: We evaluated parameter-efficient fine-tuning (PEFT) of the Segment Anything Model (SAM) for liver tumor segmentation in abdominal CT of colorectal liver

Parameter-Efficient Quantum NLP for Paraphrase Detection: Performance, Robustness, and Entanglement

arXiv:2609.14529v1 Announce Type: cross Abstract: Rigorous empirical validation of quantum machine learning on natural language tasks remains scarce. We evaluate a 10-qubit hybrid quantum-classical va

Parameter Estimation of Ringdown Quasinormal Modes with Autoencoder

model-releasesarxiv-cs-lg

arXiv:2609.14277v1 Announce Type: cross Abstract: Ringdown gravitational waves from binary black hole mergers can be modeled as superpositions of quasinormal modes (QNMs), whose frequencies and excita

Parameter isolation with domain-specific experts for incremental audio classification

model-releasesarxiv-cs-lg

arXiv:2609.14730v1 Announce Type: cross Abstract: To successfully deploy a model in time-varying environments such as streaming data prediction and sensing control, domain-incremental learning (DIL) h

PARSE: Provenance-Aware Retrieval Sanitization for Professional Domain LLM Agents

arXiv:2606.17467v3 Announce Type: replace-cross Abstract: Prompt injection defenses evaluated on synthetic benchmarks do not generalize to real enterprise documents, which are longer, denser, and inte

Tutorials

Part Grounding, Not Action Knowledge: Locating the Bottleneck in VLM Affordance Prediction

arXiv:2609.13225v1 Announce Type: new Abstract: Benchmarks agree that vision-language models reason poorly about low-level manipulation, but an aggregate accuracy score does not say which step fails.

tutorialsarxiv-cs-cv

Hardware

Partition-Aware Scheduling for Mobile Heterogeneous Inference Co-Execution

arXiv:2609.14213v1 Announce Type: cross Abstract: Modern mobile inference runs on heterogeneous platforms combining mobile GPUs with multiple CPU core clusters. Existing optimizations typically exploi

hardwarearxiv-cs-lg

Partition Scores Are Not System Scores: Deployment-Fidelity Gaps in Decomposed Algorithm Selection

arXiv:2609.13785v1 Announce Type: new Abstract: Oracle-style quantities, including virtual best solvers, selected-portfolio VBS, virtual-best encodings, and best-in-family summaries, are widely report

Pathwise Individual Rationality in Federated Learning: A Mechanism-Architecture Co-Design

arXiv:2609.14591v1 Announce Type: new Abstract: Participation in federated learning (FL) comes at a cost. Clients trade off privacy, communication, and compute costs for potentially greater gains in m

researcharxiv-cs-lg

Patient-Level, Leakage-Aware Deep Learning for Cross-Center Periapical Radiograph Classification

arXiv:2609.14703v1 Announce Type: new Abstract: Dental caries and endodontic disease are among the most common health conditions worldwide, and intraoral periapical radiographs are central to their de

PC^2-AD: Point Cloud Upsampling to Safeguard 3D Anomaly Detection with Resolution-constrained Edge Devices

arXiv:2609.14722v1 Announce Type: new Abstract: Low-cost and low-resolution sensors used in edge deployments can produce test point clouds that are substantially sparser than the normal training data.

researcharxiv-cs-cv

Pedestrian Crossing Intent Classification From Event-Based Vision Using Convolutional Spiking Neural Networks With Temporal Augmentation

arXiv:2609.13328v1 Announce Type: cross Abstract: Anticipating whether a pedestrian will cross the road is safety-critical for autonomous vehicles, requiring real-time inference under challenging cond

PeerPen: AI-Assisted Writing for Online Mental Health Peer Support

arXiv:2609.14886v1 Announce Type: cross Abstract: Online mental health communities thrive on peer support, yet those who volunteer to help often lack formal training and may struggle to articulate sup

Per-Matrix Optimality Is Not Enough: Three-Level Optimization for Low-Rank LLM Compression

arXiv:2609.15838v1 Announce Type: cross Abstract: Per-matrix singular value decomposition (SVD) truncation is Eckart-Young optimal in the whitened Frobenius norm, but errors from independently compres

Perceive, Refine, Reason: A Calibrated Pipeline for Measuring Indicators in Strategic Visual Communication on Social Media

arXiv:2609.14699v1 Announce Type: new Abstract: Visual content shapes audience perception and opinion on social media, and computational social science increasingly relies on automated tools to analyz

researcharxiv-cs-cv

Perceptual Reality Transformer: What Must an Illustration Preserve?

arXiv:2508.09852v2 Announce Type: replace-cross Abstract: How can models help people communicate unusual perceptual experiences without changing what they mean? A recognizable image is only part of th

Personalized and Explainable Blood Pressure Estimation from PPG via Hybrid CNN--Morphological Features

arXiv:2609.13190v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring using photoplethysmography (PPG) offers a promising solution for personalized healthcare. However, ex

applicationsarxiv-cs-cv

Safety

Personalizing Personal Health Interfaces: Co-Design with Generative AI

arXiv:2609.15046v1 Announce Type: cross Abstract: Personal health interfaces present wellbeing data through standardized dashboards that rarely fit how people interpret or act on it. Personalizing the

safetyarxiv-cs-ai

Phorecaster365: A Human-Supervised Reference Architecture for Hybrid Pharmaceutical Sales Forecasting and Planning Decision Support

arXiv:2609.13907v1 Announce Type: cross Abstract: Pharmaceutical sales forecasts inform planning across products, regions, and distribution channels, yet their interpretation depends on inventory avai

PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models

arXiv:2609.14973v1 Announce Type: new Abstract: We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the ph

Industry

Physical AI security startup Exein raises 270M at 1.7B valuation

Italian cybersecurity startup Exein SpA today announced that it has raised 270 million at a valuation of 1.7 billion to build security for robots, vehicles and other machines that run artificial intel

industrysiliconangle

Safety

Physical Kernel: Structured Visual Latents for Dark Manipulation

arXiv:2609.13244v1 Announce Type: cross Abstract: We study dark manipulation: after a brief lit Write encodes z0 = Enc(rgb), a policy pi(z) and open-loop dynamics f(z,a) complete contact-rich skills w

safetyarxiv-cs-cv

Physically Partitioned KVCache Format for CPU--GPU Load Balancing in MoE Inference

model-releasesarxiv-cs-lg

arXiv:2609.14507v1 Announce Type: cross Abstract: Single-GPU long-context inference with Mixture-of-Experts (MoE) models requires spilling the key-value cache (KVCache) to CPU memory. The spilled KV s

Local Ai

Physically Typed and Geometry-Aware Representations for Earth Foundation Models

arXiv:2609.13868v1 Announce Type: new Abstract: Earth-observation (EO) foundation models have become exceptionally effective at learning se mantic, high-dimensional geospatial embeddings, while modern

local-aiarxiv-cs-cv

Physics Informed Neural Network model for the dynamical study of Abdominal Aortic Aneurysm

arXiv:2609.15104v1 Announce Type: cross Abstract: We present the development and application of a three-dimensional Physics-Informed Neural Network (PINN) framework for the investigation of haemodynam

PhysMent: An Interactive Approach For LLM Reasoning In Physics Problems

arXiv:2609.13152v1 Announce Type: new Abstract: Large language models (LLMs) perform strongly on static science benchmarks, yet their ability to reason about the physical world through active experime

Pick Your Poison: Learning to Select Poison Sets for Stronger LLM Backdoor Attacks

arXiv:2609.15029v1 Announce Type: cross Abstract: Backdoor poisoning attacks add poisoned examples to otherwise-clean finetuning data, pairing a trigger with a target behavior that the model learns to

PIDS-Bench: Evaluating Prompt-Injection Detectors Under Over-Defense, Obfuscation, and Distribution Shift

arXiv:2609.15017v1 Announce Type: cross Abstract: Prompt-injection detectors are typically evaluated using aggregate F1 on in-distribution test data, which offers limited insight into behavior under d

Pilot Early, Commit Late: A Real-Options Model of Enterprise AI Adoption under Rapid Technological Progress

arXiv:2609.15919v1 Announce Type: new Abstract: Artificial intelligence presents firms with an unusual timing problem. The technology frontier is improving rapidly, implementation is partly irreversib

PIVOT: Physics-Grounded Verification for AI-Generated Audio-Video Detection

arXiv:2609.15562v1 Announce Type: cross Abstract: As generative models continue to advance, AI-generated content (AIGC) is becoming increasingly realistic, weakening the artifact cues commonly exploit

Pixel-wise Planarity for High-Precision Monocular Plane Segmentation

arXiv:2609.13246v1 Announce Type: new Abstract: Plane segmentation from a single RGB image remains challenging due to imprecise region grouping and geometrically inconsistent supervision, often leadin

researcharxiv-cs-cv

Planning as Dynamics Relaxation: Hippocampal Recurrent Network Realizes Optimal Goal-Directed Navigation

arXiv:2609.13219v1 Announce Type: cross Abstract: Neural correlates of spatial cognitive map are well documented, yet exactly how neural circuits perform spatial navigation in complex environments - e

Planning in the Backbone: DiffAdapterVLA for Native Continuous Trajectory Generation with Driving VLMs

arXiv:2609.15322v1 Announce Type: cross Abstract: Pretrained driving vision-language models (VLMs) integrate visual, route, language, and driving context into rich driving priors, yet their representa

Planning or Learning: Reliability and Cost in Multi-Asset Maintenance

arXiv:2609.13566v1 Announce Type: new Abstract: Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational co

POLARIS: Training-Free Audio Fingerprinting with Saliency-Based Landmarks and Delaunay Grouping

arXiv:2609.14820v1 Announce Type: cross Abstract: This work presents POLARIS, a training-free audio fingerprinting system that selects landmarks from a locally normalized saliency field and groups the

Policy Loopholes in Agent Evaluation: When Policy Ambiguity Masquerades as Agent Error

arXiv:2609.14400v1 Announce Type: new Abstract: Agent benchmarks evaluate policy compliance but assume each policy determines a unique correct action. Natural-language policies can violate this assump

Safety

PolicyMem: Geometric Policy Memory for LLM Governance

arXiv:2609.13734v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in real-world high-stakes applications, effective governance has become essential. Existing

safetyarxiv-cs-ai

Positioning manuscripts in the scientific landscape with agentic AI

arXiv:2609.13760v1 Announce Type: new Abstract: Publishing a research manuscript is a routine yet demanding part of scientific life: time-consuming, stressful, and often uncertain in outcome. Recent a

Positive Topology and Feasible Refinement: Forcing Matrices, Positivity, and Information

arXiv:2609.13523v1 Announce Type: cross Abstract: We develop a conceptual and operational account of Positive Topology starting from a basic relation between points or models and observable properties

Post-Reasoning: Improving the Performance of Non-Thinking Models at No Cost

arXiv:2605.06165v2 Announce Type: replace Abstract: As the widespread adoption of Large Language Models (LLMs) accelerates, token consumption from intermediate reasoning traces increasingly contribute

Potential of Artificial Intelligence Algorithms for Identification of Relevant Diagnostic and Prognostic Biomarkers of Early-Stage Liver Cancer

arXiv:2609.15638v1 Announce Type: new Abstract: This study explores the use of deep learning and explainable artificial intelligence to diagnose hepatocellular carcinoma (HCC) and define effective bio

PPDL: A Real-world Industrial User Retention Ratio Forecasting Framework Integrating Physical Priors with Deep Learning

arXiv:2609.13789v1 Announce Type: new Abstract: In multi-channel paid user acquisition, early and accurate prediction of user retention at the channel level is crucial for optimizing budget allocation

applicationsarxiv-cs-lg

Pre-PEFT Probing: Weight Statistics and Perturbation Robustness for Layer Selection in VLM Vision Encoders

arXiv:2609.15229v1 Announce Type: cross Abstract: We propose a pre-fine-tuning probing method for Parameter-Efficient Fine-Tuning (PEFT) layer selection, aiming to obtain more stable and higher gains

Pre-training with Graph Transformers

arXiv:2609.13844v1 Announce Type: new Abstract: This article investigates pre-training strategies for graph transformers in the biochemistry domain. By conducting comprehensive experiments, the study

researcharxiv-cs-lg

Predicting build orientation for SLM dental parts: a comparison of rotation representations and direct vector regression

arXiv:2609.15710v1 Announce Type: new Abstract: Build orientation for selective laser melting (SLM) manufacturing of dental parts is usually chosen manually by technicians. We treat orientation predic