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Phys4D: Fine-Grained Physics-Consistent 4D Modeling from Video Diffusion

arXiv:2603.03485v4 Announce Type: replace-cross Abstract: Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often strugg

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Physical Adversarial Examples for Person Detectors in Thermal Images Based on 3D Modeling

DGX agent

arXiv:2608.30839v1 Announce Type: new Abstract: Thermal Infrared detection is widely used in autonomous driving, medical AI, etc., but its security has only attracted attention recently. We propose in

agentsarxiv-cs-cv

1 Sept 2026

Local Ai

PhysVR: Vision-Language Model Guided Interference-aware Temporal Feature Refinement for Remote Physiological Measurement

arXiv:2608.29663v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables contactless physiological measurement from facial videos, yet its subtle pulse-related variations are easily

local-aiarxiv-cs-cv

PhysWave: Physics-Guided Latent Diffusion Models for Controllable Spatial Audio Generation

arXiv:2608.29549v1 Announce Type: cross Abstract: Text-to-spatial audio generation, such as text-to-First-Order Ambisonics (FOA), provides a convenient way to create spatial audio for billion-dollar g

Pixel-wise Geo-registration of Drone and Satellite Images

model-releasesarxiv-cs-cv

arXiv:2608.28891v1 Announce Type: new Abstract: Pixel-level cross-view geo-registration aims to align a query image (e.g., drone) to a geo-referenced satellite map so that every query pixel can be map

PixelIR: Fidelity-Perception Decoupling via Pixel-Space Image-Residual Flow Matching for Efficient One-Step Real-World Super-Resolution

arXiv:2608.30782v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) aims to preserve structures supported by the degraded observation while reconstructing perceptually realist

applicationsarxiv-cs-cv

Plant-Inspired AI: Plants as Inspiration for Novel Problem Formulations, and Two Case Studies

arXiv:2608.29356v1 Announce Type: new Abstract: Artificial Intelligence (AI) has long been inspired by studies of biological intelligence. Reinforcement learning, for instance, drew inspiration from s

applicationsarxiv-cs-ai

PLC-DPO: Posterior Label Correction in Noisy and Ambiguous Preference Optimization

model-releasesarxiv-cs-cl

arXiv:2608.30597v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) simplifies alignment through pairwise comparisons but assumes all observed preferences are reliable. Real data of

POCI-Diff: 3D-Layout Guided Diffusion for Controllable Synthetic Surveillance Data Generation

arXiv:2601.14056v2 Announce Type: replace-cross Abstract: Training robust visual surveillance models requires large-scale datasets with precise spatial annotations, yet collecting real surveillance da

PokaiTrainer: Scaling Belief-State Search to Competitive Pokemon VGC

arXiv:2608.29197v1 Announce Type: cross Abstract: Decision-time equilibrium search carried poker to superhuman play, but it has so far relied on tractable subgames: a handful of actions per decision,

agentsarxiv-cs-ai

Polis: 3D Self-Supervision at City Scale

arXiv:2608.29426v1 Announce Type: cross Abstract: Reliable semantic representations derived from city-scale 3D models are increasingly important for urban analysis, infrastructure monitoring, autonomo

Political Ideology Shifts in Large Language Models

arXiv:2508.16013v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in politically sensitive contexts, raising concerns about their susceptibility to ideological

safetyarxiv-cs-cl

Popular but Wrong: Understanding and Mitigating LLM Overconfidence through Knowledge Popularity

arXiv:2505.17537v2 Announce Type: replace Abstract: Large language models (LLMs) often produce incorrect answers with high confidence, yet the factors associated with such overconfidence remain insuff

safetyarxiv-cs-cl

post-graph-rag: A PostgreSQL-Native Bi-Temporal Graph RAG Engine with Temporal Grounding at Synthesis

arXiv:2608.24921v2 Announce Type: replace Abstract: Graph RAG connects facts no single passage states, but implementations pay three times: in infrastructure, keeping vector store, graph database and

Hardware

PowerSlider: Exploiting Phase Asymmetry for LLM Serving under Demand Response

arXiv:2608.21719v1 Announce Type: cross Abstract: AI inference clusters are increasingly constrained by instantaneous power, not just energy: grid operators condition new capacity on demand response,

hardwarearxiv-cs-ai

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation

arXiv:2402.04355v4 Announce Type: replace-cross Abstract: We propose a likelihood-free method for comparing two distributions given samples from each, with the goal of assessing the quality of generat

PRACTICE: From Experience to Expertise in Self-Evolving Embodied Agents

arXiv:2608.30760v1 Announce Type: new Abstract: Recent studies have shown that multimodal large language models (MLLMs) can serve as embodied agents, translating language instructions and visual obser

safetyarxiv-cs-lg

Predicting Future Organ Dysfunction in ICU Patients Using Temporal Convolutional Networks on MIMIC-IV Data

arXiv:2608.29301v1 Announce Type: new Abstract: Predicting future organ dysfunction in Intensive Care Unit (ICU) patients is critical for early clinical intervention, yet existing machine learning app

safetyarxiv-cs-ai

Predicting Residential Rents in Dakar Using Machine Learning

arXiv:2608.30865v1 Announce Type: new Abstract: Dakar's residential rental market remains poorly documented despite its economic and social importance: 54.4% of households are renters, compared to 23.

Tutorials

Predicting the Unpredictable: LLM-powered Long-term Chaotic Time Series Forecasting under Short-term Observations

arXiv:2608.29579v1 Announce Type: new Abstract: Chaotic time series forecasting is a challenging task due to its sensitivity to initial conditions and long-term unpredictability. Traditional methods t

tutorialsarxiv-cs-lg

Prediction-Powered Conditional Inference

arXiv:2603.05575v2 Announce Type: replace-cross Abstract: We study prediction-powered conditional inference in the setting where labeled data are scarce, unlabeled covariates are abundant, and a black

researcharxiv-cs-lg

Preference Elicitation for Policy Optimization and Application to Aligning Heart Transplantation with Human Values

arXiv:2608.28620v1 Announce Type: new Abstract: Preference elicitation is essential for aligning AI systems with human values. Prior approaches (e.g., for organ allocation) often ask stakeholders to c

safetyarxiv-cs-ai

Preference Shapes Relevance: Cross-component Hierarchical Semantic Alignment for Personalized Generative Retrieval

arXiv:2608.30553v1 Announce Type: cross Abstract: Generative Retrieval (GR) has emerged as a promising paradigm by mapping queries directly to Semantic IDs (SIDs) with powerful representation capabili

safetyarxiv-cs-ai

Tutorials

Pretrained, Curriculum-Tuned, and Ensembled: A Tracer-Aware Interactive Segmentation Pipeline for AutoPET V

arXiv:2608.30844v1 Announce Type: cross Abstract: Interactive lesion segmentation in whole-body PET/CT requires a model to provide a strong initial prediction while also responding efficiently to spar

tutorialsarxiv-cs-ai

PRIME: Mitigating Subgroup Optimization Competition in Shared CTR Top Networks with Plug-in Residual Input-Conditioned Mixture of Expert

arXiv:2608.30449v1 Announce Type: new Abstract: Click-through rate (CTR) models vary in feature-interaction design, yet their top networks usually remain a single multilayer perceptron shared by all e

researcharxiv-cs-lg

PRISM: Predictive Recomposition via Semantic Latent Decomposition for View-invariant Video Representation Learning

arXiv:2608.30388v1 Announce Type: cross Abstract: Cross-view video representation learning aims to capture viewpoint-invariant action semantics despite substantial appearance changes across egocentric

Privacy-Preserving Detection of Rare Disease-Associated Cell Subsets via Secure Multi-Party Computation

model-releasesarxiv-cs-lg

arXiv:2608.20118v1 Announce Type: cross Abstract: The detection of rare disease-associated cell subsets from high-dimensional single-cell measurements is critical for understanding diseases such as le

Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies

arXiv:2509.10882v2 Announce Type: replace Abstract: In high-stakes domains such as healthcare, privacy concerns severely limit the use of real-world training data. Differentially private (DP) syntheti

applicationsarxiv-cs-cl

Private cloud grows up as enterprises push AI into production

Enterprise infrastructure is being rebuilt around agentic AI, and the center of gravity is shifting back toward private environments where data, cost and control sit under one roof. As inference workl

agentssiliconangle

PrivBench: A Holistic and Modular Benchmarking Platform for Evaluating Text-to-Text Privatization

model-releasesarxiv-cs-cl

arXiv:2608.29624v1 Announce Type: new Abstract: Natural Language Processing methods have enabled novel solutions and advances in the field of privacy, particularly in the sub-domain of text-to-text pr

Pro-Router: Token-Aware Progressive Model Routing with Adaptive Edge-Cloud Collaboration for Efficient Multimodal LLM Inference

arXiv:2608.28726v1 Announce Type: new Abstract: The remarkable performance of multimodal large language models (MLLMs) comes at the cost of substantial computational overhead, posing significant chall

ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs

arXiv:2608.25992v2 Announce Type: replace Abstract: Multi-agent large language model (LLM) workflows have emerged as a powerful paradigm for solving complex, open-ended tasks through collaborative rea

agentsarxiv-cs-ai

ProGS: Towards Progressive Coding for 3D Gaussian Splatting

arXiv:2603.09703v2 Announce Type: replace Abstract: Progressive transmission of 3D Gaussian Splatting (3DGS) requires each completed transmission stage to be decodable from received data and directly

researcharxiv-cs-cv

ProGVC: Progressive-based Generative Video Compression via Auto-Regressive Context Modeling

arXiv:2603.17546v2 Announce Type: replace Abstract: Perceptual video compression leverages generative priors to reconstruct realistic textures and motions at low bitrates. However, existing perceptual

researcharxiv-cs-cv

Projection-Aware End-to-End Learned Video Compression for 360-Degree Video

arXiv:2608.28689v1 Announce Type: new Abstract: 360-degree video supports immersive applications such as virtual reality, autonomous driving, and education. Because spherical content cannot be process

agentsarxiv-cs-cv

PromptKWS: A Novel Prompt-Guided Open-Vocabulary Keyword Spotting Framework

arXiv:2608.28640v1 Announce Type: cross Abstract: In this paper, we present PromptKWS, a novel Prompt-guided keyword spotting (KWS) framework to improve the accuracy of open vocabulary KWS systems. In

applicationsarxiv-cs-ai

Proof2Hybrid: Automatic Mathematical Benchmark Synthesis for Proof-Centric Problems

arXiv:2508.02208v3 Announce Type: replace-cross Abstract: Evaluating the mathematical capability of Large Language Models (LLMs) is a critical yet challenging frontier. Existing benchmarks fall short,

Propensity Straight-Through Gradients for Discrete Stochastic Systems

model-releasesarxiv-cs-lg

arXiv:2608.25631v1 Announce Type: cross Abstract: Continuous-time Markov chains (CTMCs) provide the backbone for modeling discrete stochastic dynamics across applied, physical, and biological sciences

Provably Safe Decentralized Contingency MPC under State-Only Information and Limited Sensing for Nonlinear Multi-agent Systems

arXiv:2608.30874v1 Announce Type: cross Abstract: This paper considers decentralized contingency MPC for multi-agent control under a state-only information pattern, with particular focus on limited se

safetyarxiv-cs-ro

Prove2Me: An Open Collaborative Platform for Scaling Math Formalization

arXiv:2608.28433v2 Announce Type: replace Abstract: Proof assistants such as Lean 4 promise the paradigm of formally verified mathematics, but large-scale formalization projects have faced major barri

agentsarxiv-cs-ai

Proximity3D: Shape from Capacitive Proximity on Sensing Manifold

arXiv:2608.30344v1 Announce Type: new Abstract: Most shape reconstruction methods assume measurements defined over planar sensing domains, such as RGB images or depth maps. In this paper, we use a cur

researcharxiv-cs-cv

PruneShift: A Framework for Evaluating Decision Reliability in Structured Pruning

arXiv:2608.29765v1 Announce Type: new Abstract: Structured pruning uses surrogate objectives because direct task evaluation over every feasible mask is too expensive. Most evaluations report average s

researcharxiv-cs-lg

PUFFER: Incremental Fuzzy Deduplication for Continuously Evolving Corpora

arXiv:2608.28622v1 Announce Type: cross Abstract: Large language model training corpora grow through successive, often redundant releases, so each release must be deduplicated against both itself and

Pure scaling of LLMs did actually hit a wall; neurosymbolic AI rescued it. AI didn’t hit a plateau; pure LLMs did — until people used harnes…

Pure scaling of LLMs did actually hit a wall; neurosymbolic AI rescued it. AI didn’t hit a plateau; pure LLMs did — until people used harnesses and tools to complement their weaknesses. Which was alwa

safetygary-marcus--x

PyKEEN-NSX: A Modular Framework for Static, Dynamic and Schema-Aware Negative Sampling in PyKEEN

arXiv:2608.30652v1 Announce Type: new Abstract: Embedding methods have become popular due to their scalability on link prediction and/or triple classification tasks on Knowledge Graphs (KGs). Embeddin

Tutorials

Python 3.15.0 candidate 2 is here!

Python 3.15.0 candidate 2 is here! Hugo van Kemenade (release manager for Python 3.14 and 3.15) announces the final release candidate for Python 3.15, scheduled for release in October: Entering the re

tutorialssimon-willison

Q-Strata: Hierarchical Bit Allocation for Mixed-Precision Quantization of Mixture-of-Experts LLMs

arXiv:2608.30564v1 Announce Type: cross Abstract: Mixed-precision quantization (MPQ) assigns a different bitwidth to each linear layer of a large language model (LLM) to minimize the quantization-indu

QAQ: Bidirectional Semantic Coherence for Selecting High-Quality Synthetic Code Instructions

arXiv:2603.12165v3 Announce Type: replace Abstract: Synthetic data has become essential for training code generation models, yet it introduces significant noise and hallucinations that are difficult t

researcharxiv-cs-cl