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arXiv:2509.04276v3 Announce Type: replace Abstract: We present a method for modeling articulated objects from sparse images with unknown camera poses. Existing approaches require dense multi-view obse

applicationsarxiv-cs-cv

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ParA-LLM: A Unified Approach to Paralinguistic and Acoustic Speech Understanding

DGX agent

arXiv:2609.22771v1 Announce Type: cross Abstract: Recent advances in Audio LLMs have achieved human-level speech recognition, yet existing systems struggle to capture paralinguistic aspects such as sp

model-releasesarxiv-cs-lg

22 Sept 2026

Paragraph Boundaries Are Not White Space:Compression Depth as the Signature of Hierarchical Structure

arXiv:2609.23551v1 Announce Type: new Abstract: Standard positional encodings represent position as a one-dimensional reading-order coordinate, but reading order alone does not determine hierarchical

researcharxiv-cs-cl

Partial-Scan-and-Move Source Seeking for Mobile Robots

arXiv:2609.23786v1 Announce Type: cross Abstract: This paper presents a partial-scan-and-move strategy for source seeking with a mobile robot equipped with an offset scalar sensor. At each robot posit

researcharxiv-cs-ro

Patch-to-Global: Random Patch Diffusion for Globally Consistent Megapixel Artifact Inpainting in Whole Slide Images

arXiv:2609.24116v1 Announce Type: new Abstract: Although deep learning has advanced Whole Slide Image (WSI) Analysis, tissue artifacts like bubbles and folds often cause silent failures by concealing

researcharxiv-cs-cv

Pay More Attention To Text In High-Resolution MLLMs

arXiv:2609.23495v1 Announce Type: new Abstract: Failures of high-resolution MLLMs are commonly attributed to a visual problem, motivating zooming, cropping, and related visual interventions to recover

researcharxiv-cs-cv

People got upset at me for saying this, but there are no companies outside the US and China even trying to build frontier AI (perhaps Kore…

model-releasesethan-mollick--x

People got upset at me for saying this, but there are no companies outside the US and China even *trying* to build frontier AI (perhaps Korea and UK are close), despite marketing claims. Governments s

Tutorials

People outside the AI labs should have a real say in how this technology develops, and a clear way to judge if it's happening safely. Standa…

People outside the AI labs should have a real say in how this technology develops, and a clear way to judge if it's happening safely. Standards should help prevent the concentration of power, includin

tutorialssam-altman--x

Per-Query Gating of LLM Rerankers for Multi-Hop Retrieval

arXiv:2609.22880v1 Announce Type: cross Abstract: LLM rerankers add of the order of $0.2-0.3 per 1,000 queries and about a second of tail latency on top of a graph-augmented dense pipeline such as Hip

researcharxiv-cs-cl

Performance-Preserving Online Adaptation in Social Navigation via Diffusion Steering

arXiv:2609.24317v1 Announce Type: new Abstract: In social navigation, modeling the complex interactions between humans and robots is difficult, and deep reinforcement learning has therefore been activ

safetyarxiv-cs-ro

Performance vs Consistency: Evaluating a Foundation Model in Lung-RADS Screening

arXiv:2609.22281v1 Announce Type: new Abstract: Foundation models have recently demonstrated strong capabilities across a wide range of medical imaging tasks. However, their performance in structured

Perplexity Cost Understates What Activation Quantisation Breaks

arXiv:2609.23125v1 Announce Type: new Abstract: Activation quantisation is usually evaluated with an aggregate metric, perplexity, averaged over every token a model predicts. We ask whether that avera

Perplexity Predicts Protection: Choosing Pretrained Backbones for Worst-Client Fairness in Federated Parameter-Efficient Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2609.23463v1 Announce Type: new Abstract: Federated learning lets multiple parties train a shared model without pooling their data, but a client with far less data than the others can end up poo

Personalized Federated Reinforcement Learning via Model-Agnostic Meta-Learning: Convergence of Exact and Hessian-Free Meta-Policy Gradients

arXiv:2609.22833v1 Announce Type: new Abstract: We study personalized federated reinforcement learning, in which n agents, each acting in its own Markov decision process, collaborate through a server

PETR: Prompt Ensembling with Training-free Routing for Vision-Language Models

arXiv:2609.23600v1 Announce Type: new Abstract: Prompt learning efficiently adapts vision-language models (VLMs) to downstream tasks, but gains on seen classes often come at the expense of generalizat

Local Ai

Pharmacokinetic State Space Models for Unbiased Prediction of Haemodynamic Collapse

arXiv:2609.24338v1 Announce Type: new Abstract: An Intraoperative Hypotension (IOH) event is a frequent complication during administration of general anaesthesia with serious downstream consequences,

local-aiarxiv-cs-lg

Phrase-Level Robotic Guqin Performance: Bimanual Motion Planning and Audio-Tactile Interaction Monitoring

model-releasesarxiv-cs-ro

arXiv:2609.24133v1 Announce Type: new Abstract: Recent advances in humanoid robotics and embodied intelligence have enabled robots to perform increasingly complex manipulation tasks. However, musical

Agents

Physical-Touch Observability from Wrist Wrench in Granular Scooping

arXiv:2609.22852v1 Announce Type: new Abstract: Mining and earthmoving are important real-world deployment settings for embodied intelligence. Autonomous transport and driving systems have improved su

agentsarxiv-cs-ro

Physics-Informed Classical and Quantum Neural Networks for One-Dimensional Schrodinger Eigenvalue Problems

arXiv:2609.22189v1 Announce Type: cross Abstract: The Schrodinger equation in one spatial dimension admits a small set of exactly solvable potentials that serve as natural proving grounds for any new

Physics-residual machine learning predicts oxygen-evolution catalyst activity beyond the training range from sparse polarization measurements

arXiv:2609.23549v1 Announce Type: new Abstract: Screening oxygen-evolution catalysts on combinatorial libraries requires deciding which candidates receive the remaining measurements. The deciding acti

PhysReflect: Geometry and Perception Guided Diffusion for Physically-Plausible Mirror Reflections

arXiv:2609.23442v1 Announce Type: new Abstract: Diffusion models generate high-quality images, yet often violate the physical laws governing mirror reflections. Reflections often suffer from geometric

safetyarxiv-cs-cv

Applications

PICID: Proof-Driven Clause Learning in Neural Network Verification

arXiv:2503.12083v3 Announce Type: replace-cross Abstract: Current Deep Neural Network (DNN) verifiers are typically designed to prioritize scalability over reliability. Reliability can be reinforced t

applicationsarxiv-cs-lg

PII-TRACE: A Benchmark for Context-Aware PII Detection in Multi-Turn LLM Conversations

model-releasesarxiv-cs-cl

arXiv:2609.22200v1 Announce Type: new Abstract: LLM assistants and agentic systems log long multi-turn conversations. AI providers often scan these conversations for Personally Identifiable Informatio

Local Ai

PileBelief: Persistent Physical State for Interaction-Driven World Modeling

arXiv:2609.22858v1 Announce Type: new Abstract: World models allow robots to anticipate action consequences before execution. This capability is especially valuable in excavation, where each scoop res

local-aiarxiv-cs-ro

PINGU: Extending Air-Bearing Spacecraft Emulators with Open-Source Actuators and Learned Control for Contact-Rich Proximity Operations

model-releasesarxiv-cs-ro

arXiv:2609.23554v1 Announce Type: new Abstract: Low-cost planar air-bearing testbeds have matured into a standard proxy for free-flying spacecraft GNC, but they remain largely thruster-only and are ra

PixelART: Image-to-Layer Decomposition without Latents or Text-to-Image Pretraining

arXiv:2609.22789v1 Announce Type: new Abstract: Image-to-layer decomposition converts a flattened image into editable RGBA layers, enabling element-level editing in design workflows. Existing diffusio

Tutorials

PixelDiT2: Representation-Grounded Pixel Diffusion Transformers

arXiv:2609.24919v1 Announce Type: new Abstract: Recent advances in pixel-space diffusion models have narrowed the image quality gap with latent-space diffusion, but still converge more slowly and lag

tutorialsarxiv-cs-cv

Planning-Aligned Pretraining of BEV Representations with Sparse Action-Conditioned Targets for End-to-End Autonomous Driving

arXiv:2609.22868v1 Announce Type: new Abstract: End-to-end driving requires planning-relevant bird's-eye-view (BEV) representations, but existing pretraining approaches often rely on task annotations

Planning and Rendering in Concert: DeepFusion of Autoregressive Layouts and Diffusion for Visual Text Generation

arXiv:2609.22916v1 Announce Type: new Abstract: Generating text-rich images from prompts requires both textual fidelity and the coherent integration of text into the surrounding image. An explicit lay

Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of…

Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more affordable models to sup

model-releasesopenai--x

Poisson Exchange Beyond Submodularity: Effective Approximation Algorithms for Offline and Online Subset Selection over Matroids

arXiv:2609.24569v1 Announce Type: cross Abstract: Over the past decade, a growing body of research has shown that gamma-weak submodularity broadly arises in numerous subset selection tasks, including

Local Ai

PosEviLoc: Position-Conditioned Spatial Evidence for Language-Based 3D Localization

arXiv:2609.23534v1 Announce Type: new Abstract: Language-based 3D localization retrieves the point-cloud submap containing a target position from descriptions of nearby objects and their spatial relat

local-aiarxiv-cs-cv

Positive Pair Geometry Matters: Optimal Transport for Contrastive Learning of Visual Representations

arXiv:2609.24125v1 Announce Type: new Abstract: Contrastive self-supervised learning has achieved strong performance by learning representations from multiple augmented views of the same image. Howeve

PredActor: Predictive Action Diffusion for Steerable Onboard Humanoid Control

arXiv:2609.24840v1 Announce Type: cross Abstract: Diffusion models offer flexible motion generation, but translating this flexibility into feedback-responsive humanoid control remains challenging. Hie

Predicting magnetism with first-principles AI

arXiv:2602.09093v2 Announce Type: replace-cross Abstract: Computational discovery of magnetic materials remains challenging because magnetism arises from the competition between kinetic energy and Cou

Predicting Out-of-Distribution Generalization of Neural Operators via Observable Spectral Error Decomposition

arXiv:2609.23529v1 Announce Type: new Abstract: Neural operators have emerged as powerful surrogates for solving partial differential equations (PDEs), yet their reliability under distribution shift r

Agents

Prediction of Nonlinear Oscillations in a Jumping Quarter-Car Model Using Reservoir Computing

arXiv:2609.22205v1 Announce Type: new Abstract: Reliable prediction of vehicle dynamics is essential for smart driving applications such as autonomous control and advanced driver-assistance systems. O

agentsarxiv-cs-lg

Predictors and Orchestrators: Parsimonious Machine Learning within an Agentic AI Harness for Multi-Horizon Karst Aquifer Forecasting

arXiv:2609.22251v1 Announce Type: new Abstract: Forecasting karst aquifer dynamics is difficult because recharge responses are nonlinear, event-driven, and governed by strongly heterogeneous flow path

Hardware

PREM: Prefix-Steered Recurrent Memory for Long-Video Understanding

arXiv:2609.23601v1 Announce Type: new Abstract: Long-video understanding must capture transient visual evidence under strict token budgets, yet existing methods compress frames, append memory tokens,

hardwarearxiv-cs-cv

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma by Integrating Multimodal Ultrasound and Clinical Data: A Multicenter Study

arXiv:2609.24524v1 Announce Type: new Abstract: Background: Microvascular invasion (MVI) predicts recurrence and survival in hepatocellular carcinoma (HCC) but requires postoperative histopathology fo

researcharxiv-cs-cv

Prescribed-Time Contracting-Boundary Control of a Tendon-Driven Flexible Arm

arXiv:2609.22963v1 Announce Type: new Abstract: This study develops a prescribed-time performance-shaping control method for curvature tracking of a single-segment flexible arm actuated by three antag

researcharxiv-cs-ro

Prescriptive SVD-Inspired Attention via Spectral Energy Retention

arXiv:2609.24370v1 Announce Type: cross Abstract: Self-attention is central to modern Transformer architectures, but its dense dot-product formulation makes it difficult to identify which internal dir

safetyarxiv-cs-cv

Preserving Geometric Integrity in Graph Prompting via Measure-Constrained Optimal Transport

model-releasesarxiv-cs-lg

arXiv:2609.23547v1 Announce Type: new Abstract: Graph prompt learning enables parameter-efficient adaptation of frozen Graph Neural Networks to downstream tasks through lightweight prompt parameters.

Applications

Preserving What Matters: Semantic Scaffolds Beyond Saturation in Summarization Evaluation

arXiv:2609.22603v1 Announce Type: new Abstract: Summarization ships in countless production systems, making model selection a routine decision that depends on measuring summary quality. Existing metri

applicationsarxiv-cs-cl

Pretrained Persona Mixture Models and Tandem Models for Human Simulation

arXiv:2609.22607v1 Announce Type: new Abstract: We argue here that the current dominant practice in LLM human simulation: prompting instruction-tuned assistant language models to role-play personas, i

researcharxiv-cs-cl

PRIMO: Prior-Informed Odometry from Human-Motion Tracking for Humanoid Robots

arXiv:2609.23610v1 Announce Type: new Abstract: Simulation-trained humanoid proprioceptive odometry faces two transfer challenges: training trajectories generated by specific robot control policies in

safetyarxiv-cs-ro

Prior-Amortized In-Context Bayesian Inference for Generalized Linear Mixed-Effects Models

model-releasesarxiv-cs-lg

arXiv:2609.24422v1 Announce Type: new Abstract: Hierarchical data is ubiquitous in the empirical sciences and is most commonly analyzed with generalized linear mixed-effects models (GLMMs). Bayesian i

Prioritized Rollouts for Efficient World Model-based Vision-Language-Action Policy Optimization

arXiv:2609.22879v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for embodied intelligence, but fine-tuning them with reinforcement learning (RL)