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Precise Editing and Flexible Referencing for Interactable Worlds

arXiv:2609.34470v1 Announce Type: new Abstract: We present EditWorld, a video world model for precise editing and flexible referencing in interactable worlds. Existing video world models primarily foc

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Predicting Block-Coordinate Performance via Cross-Curvature

DGX agent

arXiv:2609.33489v1 Announce Type: new Abstract: Simultaneous and sequential block updates are two basic optimization strategies used across machine learning, such as neural-network training, federated

model-releasesarxiv-cs-lg

29 Sept 2026

Predicting Delayed Train Trajectories on the Dutch Railway Network: Explainable AI Evaluation of Topological, Operational and Weather Features with Tree Based Ensemble Methods

arXiv:2609.34692v1 Announce Type: new Abstract: The reliable prediction of passenger train delays is a critical component of railway management. While contemporary research frequently attempts to maxi

Applications

Predicting the Financial Impact of Supply Chain Risk for Major AI-Related Semiconductor Firms: A Heterogeneous Graph Patch Transformer Approach

arXiv:2609.32741v1 Announce Type: new Abstract: Modern semiconductor production relies on a globally distributed, multi-tier supply chain in which financial stress at one firm spreads with a delay and

applicationsarxiv-cs-lg

Predicting the Next State Is Not Enough: JEPA Representations for Lean Theorem Proving

arXiv:2609.32908v1 Announce Type: new Abstract: Neural theorem provers must both propose tactics and decide which valid successor states to explore. We study whether one-step Lean transitions provide

Prediction Limits and Koopman Closure of Geometry-Induced Soft State Abstractions

arXiv:2609.32652v1 Announce Type: cross Abstract: We study when geometry-induced soft state abstractions admit accurate finite-dimensional linear dynamics. Each state is represented by simplex-valued

Tutorials

Predictive Dual Smoothing for Column Generation

arXiv:2609.34740v1 Announce Type: new Abstract: Solving large-scale linear programs efficiently is an important challenge in many optimization settings. A key technique is column generation, which alt

tutorialsarxiv-cs-lg

Predictive Semantic Safety: From Visual Physical Reasoning to Safety-Critical Control

arXiv:2609.34356v1 Announce Type: cross Abstract: Physical interactions can create future hazards that are not apparent from the robot's current geometric surroundings. We present a framework termed P

Applications

PredRA: Fast Medical Image Translation by Deterministic Component Extraction and Controlled Stochastic Refinement

arXiv:2609.31912v1 Announce Type: new Abstract: Strongly paired medical image translation contains a substantial component that can be predicted directly from the source. The current reality is that p

applicationsarxiv-cs-cv

Preference-Guided Adaptation for Open-Vocabulary Semantic Segmentation via Prompt Disagreement

arXiv:2609.34528v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) enables pixel-level prediction over arbitrary text-specified vocabularies and has shown strong generalizati

Prefill-Free Cross-Family KV Cache Transfer for Heterogeneous Multi-Agent LLMs

arXiv:2609.32259v1 Announce Type: cross Abstract: Recent multi-agent LLM systems increasingly combine heterogeneous models for specialized agent roles. However, text-based communication requires each

Agents

PrefillShare: A Shared Prefill Module for KV Reuse in Multi-LLM Disaggregated Serving

arXiv:2602.12029v2 Announce Type: replace Abstract: Multi-agent systems increasingly orchestrate multiple specialized language models to solve complex real-world problems, often invoking them over a s

agentsarxiv-cs-lg

Hardware

PrefLUT: Reusable and Refinable Personalized Color Editing from Pairwise Preferences

arXiv:2609.34133v1 Announce Type: new Abstract: Photographic color editing is inherently personal: the same image can appear too warm, too muted, or already satisfactory to different users. Most looku

hardwarearxiv-cs-cv

Presence Is Not Faithfulness: Figurative Vehicle Intrusion in Text-to-Image Generation

arXiv:2609.32188v1 Announce Type: new Abstract: Text-to-image (TTI) models increasingly generate high-quality images from natural-language prompts, yet figurative language exposes a failure: a vehicle

Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction

arXiv:2609.33928v1 Announce Type: new Abstract: Predicting spatial gene expression from histology images could scale spatial transcriptomics (ST) to image-only cohorts, but conventional histology-base

Pretraining Transformers with Quantized Softmax in Attention

arXiv:2609.33591v1 Announce Type: new Abstract: Low-precision Transformer systems increasingly quantize attention matrix multiplications, while softmax often remains at higher precision. During pretra

Price Stability in the European Union: A Systemic Approach Using Random Matrix Theory

arXiv:2609.35011v1 Announce Type: new Abstract: Price stability remains a pillar in monetary policy practices and carries a special importance within monetary unions. Mainstream economics tried to lev

Principal Steering Subspaces for Online Adaptation of Frozen Generative Robot Policies

model-releasesarxiv-cs-ro

arXiv:2609.33765v1 Announce Type: new Abstract: Generative robot policies provide expressive behavior priors, but updating a large diffusion or flow-matching model through online interaction is costly

Printability-Constrained Adversarial Decals for Near-Nadir Aerial Perception: Measured Ink Gamuts, Nested Realism Constraints, and a Physical-World Bound

arXiv:2609.33513v1 Announce Type: new Abstract: Adversarial patches for aerial perception are typically evaluated as digital composites, with printing left as an implementation detail. This study impo

Prioritizing Repeated LLM Evaluation for Hidden Failure Discovery

arXiv:2609.32547v1 Announce Type: new Abstract: Large language models are commonly evaluated by generating a small number of stochastic responses for each prompt in a benchmark. Because inference budg

PrismQuant: Optimal Null-Space Rotations for Grouped Quantizers

arXiv:2609.32429v1 Announce Type: cross Abstract: Smaller activation outliers do not necessarily imply better low-bit quantization: their alignment with the quantizer matters. We introduce PrismQuant,

Privacy-Preserving Full-Body Meshing from mmWave Radar via Mesh Foundation Model Supervision

arXiv:2609.34768v1 Announce Type: cross Abstract: Millimeter-wave (mmWave) radar enables privacy-preserving human perception, but the extreme sparsity of point clouds from commercial single-chip senso

PROACT-Agent: Progressive Runtime Oversight and Active Circuit-breaking for Real-Time Safety

arXiv:2609.34415v1 Announce Type: new Abstract: The transition from Large Language Models (LLMs) to agents shifts safety stakes from toxic text to irreversible environmental harm. While current defens

Proactive Motion Planning for Human-Robot Cooperation

arXiv:2609.32354v1 Announce Type: new Abstract: This abstract addresses the incorporation of human motion prediction into proactive and dynamic human-aware motion planning, with the goal of enabling s

researcharxiv-cs-ro

Applications

Probabilistic electrical power demand forecasting with uncertainty quantification

arXiv:2609.34120v1 Announce Type: new Abstract: The majority of research on electricity consumption forecasting has focused on deterministic approaches, which generate a single point estimate for each

applicationsarxiv-cs-lg

Probabilistic Geodesic Flow Matching on Location-Scale Families

arXiv:2609.34613v1 Announce Type: cross Abstract: Flow matching (FM) has recently emerged as a promising framework for generative modeling due to its conceptual simplicity and strong empirical perform

Probe to Act: Elevating Browser-Use Agent via Active Visual Probing

arXiv:2609.33646v1 Announce Type: cross Abstract: Browser-use agents require seamless alignment between structured web metadata and visual information, while preserving relevant context across long in

Product-Aware Deterministic Rounding for Quantized Matrix Multiplication

arXiv:2609.31641v1 Announce Type: new Abstract: Scalar rounding decisions interact through matrix multiplication. We study deterministic product-aware rounding after scales, clipping bounds, and grids

ProDyGS: Dynamic Gaussian Splatting from a Single Static Monocular Camera

arXiv:2609.32711v1 Announce Type: new Abstract: We present ProDyGS, a novel dynamic 3D Gaussian Splatting framework for high-quality novel view synthesis from videos captured by a single static camera

Program-Verified Self-Evolution for Vision-Language Models

arXiv:2609.33855v1 Announce Type: new Abstract: Self-evolving vision-language models train on questions they generate from unlabeled images. Since these questions have no gold answers, prior methods l

Progressive Risk Estimation for Accident Anticipation

arXiv:2609.32811v1 Announce Type: new Abstract: Accident anticipation aims to recognize anomalous driving cues before a crash while avoiding false alarms during normal driving. Existing approaches typ

Progressive-View On-Policy Distillation for Regional-to-Global Transfer in Multimodal LLMs

arXiv:2609.32333v1 Announce Type: new Abstract: Regional-to-global distillation uses crop-conditioned guidance to improve full-image understanding. The challenge is to effectively transfer the teacher

safetyarxiv-cs-cv

Local Ai

Projective Normal Fields: A Convex Optimization Method for Constructing Smooth UDFs

arXiv:2609.34784v1 Announce Type: new Abstract: Constructing a smooth approximation of an unsigned distance field (UDF) from a raw point cloud is challenging because the input provides neither surface

local-aiarxiv-cs-cv

Prompt-Anchored Residual Adaptation for Biomedical Vision-Language Models

arXiv:2609.33701v1 Announce Type: new Abstract: Pretrained biomedical vision-language models achieve strong zero-shot performance in biomedical image classification. However, downstream biomedical cla

Prompting Particle Physics: Tokenized Multi-modal Foundation Models for Combinatorially Many Tasks

arXiv:2609.31862v1 Announce Type: cross Abstract: Reconstruction and simulation at a collider experiment are long chains of specialised algorithms, each tuned to a single step. We explore how one mode

Propagate, Then Sharpen: Post-Hoc Refinement of Frozen Node Classifiers

arXiv:2609.35080v1 Announce Type: new Abstract: We study post-hoc refinement of frozen node classifiers: given only the graph G and class distributions Q predicted by a frozen model, can we improve ac

Proprioceptive Force Estimation for Quadruped Locomotion and Human-Robot Interaction

arXiv:2609.34222v1 Announce Type: new Abstract: Payload forces must be accommodated during locomotion, while leash forces can specify desired motion. We investigate whether a shared three-dimensional

safetyarxiv-cs-ro

Prosodic ABX: A Language-Agnostic Method for Measuring Prosodic Contrast in Speech Representations

arXiv:2604.02102v2 Announce Type: replace-cross Abstract: Speech representations from self-supervised speech models (S3Ms) are known to be sensitive to phonemic contrasts, but their sensitivity to pro

Agents

Prospective Interpretation Risk: Principled Communication Control Between LLMs

arXiv:2609.33885v1 Announce Type: cross Abstract: Large language model (LLM) agentic systems increasingly rely on models communicating with one another, yet existing uncertainty and multi-agent method

agentsarxiv-cs-lg

Protected Cores Are Not Enough: Certifying AI-Proposed Revisions of Temporal Specifications

arXiv:2609.33461v1 Announce Type: cross Abstract: Runtime monitoring traditionally evaluates a specification that is fixed before execution or externally modified when requirements change. In learning

ProtoSeam: Lifting Classifier Training with Latent Gaussian Mixture Models

arXiv:2609.35174v1 Announce Type: new Abstract: We propose a lifted reformulation of supervised classification that improves the final accuracy of standard classifiers without changing the architectur

Provable Benefits of Regularization: Fast Rates for Adversarial Imitation Learning

arXiv:2609.35698v1 Announce Type: new Abstract: We study adversarial imitation learning (AIL), in which an agent learns to imitate expert demonstrations by optimizing a policy against an adversarial r

Proxy2World: Learning to Generate Worlds From Lightweight Proxies without Seeing Them

arXiv:2609.35023v1 Announce Type: new Abstract: Lightweight scene proxies let creators control scene layout and motion while leaving room for imagination in appearance, lighting, and visual effects. H

PruneForget: Joint Unlearning and Pruning of Vision Models

arXiv:2609.32162v1 Announce Type: new Abstract: Machine unlearning and model pruning are increasingly coupled in the real world. Models must support unlearning requests, e.g., for safety concerns, whi

safetyarxiv-cs-cv

PSM: Dataset Distillation Based on Precise Statistical Matching by Difficulty

arXiv:2609.34299v1 Announce Type: new Abstract: Dataset distillation (DD) condenses a large original dataset into a small distilled dataset with high training utility. Decoupled statistical matching m

Local Ai

PULSE: Identifying Demonstration-Utility Features with Sparse Autoencoders

arXiv:2609.32469v1 Announce Type: cross Abstract: In-context learning is highly sensitive to demonstration choice, yet most methods select demonstrations using external query-demonstration similarity.

local-aiarxiv-cs-lg

Pulseflow: PPG Counterfactual Generation Via Latent Transport

arXiv:2609.33501v1 Announce Type: new Abstract: Photoplethysmography (PPG) has become an important modality for continuous cardiovascular monitoring, including atrial fibrillation (AF) detection. Howe

Hardware

PulseInfer: I/O-Centric Sparse KV Cache Offloading for Efficient Long-Context LLM Decoding

arXiv:2609.34555v1 Announce Type: new Abstract: Long-context LLM serving is increasingly bottlenecked by decode, where large KV caches limit batch size and underutilize GPUs. Sparse KV cache offloadin

hardwarearxiv-cs-lg