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PCT-Prompt: A Prompt-Guided Transformer Framework for Dense Prediction Tasks in Point Clouds

arXiv:2608.16225v1 Announce Type: new Abstract: Standard Transformers have proven effective in point cloud object classification, but their performance in dense prediction tasks within complex scenes

applicationsarxiv-cs-cv

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PDDLCoder: Agentic PDDL Generation for LLM-Assisted Symbolic Planning

DGX agent

arXiv:2608.16637v1 Announce Type: new Abstract: LLMs remain unreliable for long-horizon planning, often generating logically inconsistent or non-applicable plans. Recent hybrid methods instead transla

model-releasesarxiv-cs-ai

18 Aug 2026

PE-CSNet: An equivariant network architecture with learnable patch-based sparse representation

arXiv:2608.14708v1 Announce Type: new Abstract: Compressive sensing (CS) enables accurate signal reconstruction from sparse measurements and is widely applied in medical imaging, remote sensing, and i

PerFACT: Motion Policy with LLM-Powered Dataset Synthesis and Fusion Action-Chunking Transformers

model-releasesarxiv-cs-ro

arXiv:2512.03444v2 Announce Type: replace Abstract: Deep learning methods have significantly enhanced motion planning for robotic manipulators by leveraging prior experiences within planning datasets.

Periocular Soft Biometrics: A Survey and Applications to Multimedia Forensics and Disinformation Detection

arXiv:2608.14701v1 Announce Type: new Abstract: Soft-biometric attributes such as gender, age, and ethnicity provide valuable ancillary evidence when full identity recognition is not feasible, support

safetyarxiv-cs-cv

PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification

arXiv:2608.15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as

applicationsarxiv-cs-lg

PersonaDrive: Controllable Trajectory Prediction with Multi-Dimensional Driving Personas

arXiv:2608.15230v1 Announce Type: new Abstract: Although recent trajectory prediction and end-to-end autonomous driving methods improve robustness in urban environments, they still lack meaningful con

agentsarxiv-cs-cv

Personalized Auto-Research: Towards a True AI Co-Scientist

arXiv:2608.14881v1 Announce Type: new Abstract: AI co-scientists that generate hypotheses, retrieve related work, design experiments, execute code, and draft full papers are beginning to change how re

PersonaShot: Benchmarking Person-Centric Narrative Continuity in Multi-Shot Video Generation

arXiv:2608.16717v1 Announce Type: new Abstract: Video generation is rapidly evolving from single-shot clips to multi-shot narratives, where the human character serves as the core narrative anchor. How

Local Ai

Perspective-Invariant Attack with Enhanced Transferability of Adversarial Examples

arXiv:2608.15115v1 Announce Type: new Abstract: Adversarial examples generated on a surrogate deep neural network (DNN) can often successfully fool other black-box DNN models. This cross-model transfe

local-aiarxiv-cs-cv

PertMind: Eliciting Emergent Biological Reasoning in LLM via Reinforcement Learning on Cellular Perturbation Data

arXiv:2608.16419v1 Announce Type: cross Abstract: Large language models can describe mechanisms, yet scalable post-training still depends on costly, manually curated biological reasoning traces. Here

Phase-Aware CNN for Real-Time 5G/6G Channel Estimation with Hardware-in-the-loop Validation

arXiv:2608.14676v1 Announce Type: cross Abstract: In 5G/6G wireless systems, accurate and timely channel estimation is critical to ensure reliable communication under complex, fast-changing radio cond

researcharxiv-cs-lg

PhaseLoRA: Control-Regime-Conditioned Low-Rank Adaptation for Continuous-Action Vision-Language-Action Policies

arXiv:2608.15285v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) is a natural way to adapt pretrained vision-language-action (VLA) policies, but most adapter designs apply temp

Physics-informed VAE-EVT for Tail Aware Radio Map Prediction

arXiv:2608.15314v1 Announce Type: new Abstract: Ultra-reliable low-latency communication (URLLC) requires precise identification of spatial regions where the signal-to-noise ratio (SNR) falls below an

Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents

arXiv:2608.16578v1 Announce Type: new Abstract: AI agents increasingly operate as part of interacting systems rather than in isolation. As agents exchange information and jointly make decisions, their

agentsarxiv-cs-ai

Physiological World Models for Human State Transitions

arXiv:2608.15309v1 Announce Type: new Abstract: Continuous multimodal sensing now allows human physiology to be observed throughout daily life rather than only during occasional clinical visits. Howev

PhyxMamba: Chaotic System Reconstruction from Short Context Observations with Generative State-Space Models

arXiv:2505.23863v3 Announce Type: replace-cross Abstract: Understanding chaotic dynamics is a fundamental problem across scientific disciplines, including climate science, neuroscience, and fluid dyna

applicationsarxiv-cs-ai

Picking the Right Image to Classify: Reliable-Input Selection in Teledermatology

arXiv:2608.16198v1 Announce Type: cross Abstract: Dermatology models face distribution shifts in teledermatology settings, where submitted images differ from the training data in lighting, angle, dist

PickStyle: Video-to-Video Style Transfer with Context-Style Adapters

arXiv:2510.07546v2 Announce Type: replace Abstract: We address the task of video style transfer with diffusion models, where the goal is to preserve the context of an input video while rendering it in

safetyarxiv-cs-cv

pico-type: A 1.5M-Parameter Byte-Level Multi-Head Content Classifier

arXiv:2608.14658v1 Announce Type: cross Abstract: We introduce pico-type, a byte-level multi-head content classifier with approximately 1.5 million parameters that simultaneously predicts seven conten

Tutorials

PIKFNO: An Interpretable Neural Operator Based on Physics Informed Kernel Function

arXiv:2608.14619v1 Announce Type: new Abstract: This work proposes a new interpretable neural operator framework, termed the Physics Informed Kernel Function Neural Operator (PIKFNO), which explicitly

tutorialsarxiv-cs-lg

PixelControl: Fine-Grained Condition Fidelity in Text-to-Image Diffusion

arXiv:2608.15705v1 Announce Type: new Abstract: Controllable text-to-image diffusion models can often follow the global layout of spatial conditions, yet still violate fine-grained structures such as

researcharxiv-cs-cv

PixRestore: Unified Image Restoration via Pixel Diffusion Transformer

arXiv:2608.16793v1 Announce Type: new Abstract: Unified image restoration (UIR) aims to recover high-quality (HQ) content from low-quality (LQ) images with different degradations using a single model.

PL-Guard: Probabilistic Logic Reasoning for LLM Guardrails

arXiv:2608.15673v1 Announce Type: cross Abstract: Large language model guardrails can be viewed as policy-consistency problems: a system must determine which policy-relevant facts hold in a prompt-res

Planner-Conditioned Diffusion for Coordinated Multi-Agent Exploration

arXiv:2608.16229v1 Announce Type: new Abstract: Coordinated multi-agent exploration requires not only efficient individual coverage but also non-redundant coverage across agents over extended planning

safetyarxiv-cs-ro

Platform Adaptation Under Governance Interventions: Actor Best-Response Modeling and an External Public-Case Benchmark

arXiv:2608.15131v1 Announce Type: new Abstract: Digital platforms govern by changing rules: rankings, monetization thresholds, moderation standards, verification systems, disclosure requirements, appe

Plausible but Not Valid: A Psychometric Audit of LLMs as Synthetic Survey Respondents

arXiv:2608.14606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic survey respondents, but existing evaluations ask whether answers look plausible at the

applicationsarxiv-cs-ai

PLeDO: Pain Level Detection for Osteoarthritis from EMR Data

arXiv:2608.15719v1 Announce Type: new Abstract: Osteoarthritis (OA) is a progressive chronic joint disease resulting in a breakdown of articular cartilage and bone when damaged joint tissues are not a

PLSQLBench: Benchmarking LLM Systems for Executable Procedural Database Programming

model-releasesarxiv-cs-cl

arXiv:2608.15931v1 Announce Type: new Abstract: We present PLSQLBench, to our knowledge the first benchmark for evaluating whether LLMs can write executable PL/SQL programs, with correctness measured

Tutorials

Pluralistic Human-Robot Interaction: Designing for Robot Interaction with Diverse Communities

arXiv:2608.16049v1 Announce Type: cross Abstract: Social robots are being developed for homes, schools, and other environments where they will interact with diverse users. While Human-Robot Interactio

tutorialsarxiv-cs-ro

POI Recommendation with LLM-Augmented Multi-Graph Learning and Contrastive Alignment

arXiv:2608.16407v1 Announce Type: cross Abstract: Point-of-interest (POI) recommendation models based on graph neural networks achieve strong performance by propagating collaborative signals over user

safetyarxiv-cs-lg

Pointer Networks with Q-Learning for Combinatorial Optimization

arXiv:2311.02629v5 Announce Type: replace Abstract: We introduce the Pointer Q-Network (PQN), a hybrid neural architecture that integrates model-free Q-value policy approximation with Pointer Networks

safetyarxiv-cs-lg

Policy Iteration with Human Feedback: Bringing Post-Training RL to In-context Learning

arXiv:2608.16831v1 Announce Type: new Abstract: Generative pretraining established reusable task representations; later work on language-based task conditioning and in-context learning showed that a f

PolyComp: A Polycube-based Benchmark for Compositional 3D Spatial Reasoning in Multimodal Models

arXiv:2608.14741v1 Announce Type: cross Abstract: We introduce PolyComp, a procedurally generated and verified benchmark that stresses visual recognition and compositional spatial reasoning. In each p

PolyDebate: A Game-Orchestrated Multimodal System for Debate Skills Practice and Evaluation

arXiv:2608.16276v1 Announce Type: cross Abstract: Debate is a structured form of persuasive communication that trains argument construction, rebuttal, oral delivery, and audience awareness. These skil

applicationsarxiv-cs-cl

Population Structure Analysis of an Inbred Population using Quantitative Shape Phenotyping from Stereo Retinal Photographs

arXiv:2608.15471v1 Announce Type: cross Abstract: The population structure of an inbred population of 781 people on Norfolk Island in the Pacific, 318 of which are descendants of the original Mutineer

researcharxiv-cs-cv

PoseAdapter: Dual-Stream 2.5D Controllable Image Generation for Complex Multi-Object Scenes

arXiv:2608.15583v1 Announce Type: new Abstract: While Text-to-Image (T2I) diffusion models have achieved remarkable success, precise spatial and orientational control in multi-object scenes remains a

researcharxiv-cs-cv

Position: AI Agents in Scientific Teams Should Be Studied as Human-Agent Systems

arXiv:2608.14667v1 Announce Type: new Abstract: Large language model-based agents are increasingly deployed as collaborators in scientific discovery yet most current work focuses on the autonomous cap

agentsarxiv-cs-ai

Position: AI Governance Needs ISO-like Interoperability Protocols, Not Just Laws

arXiv:2608.14568v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems become deeply integrated into critical global infrastructure, the urgency for robust governance frameworks has i

safetyarxiv-cs-ai

Position: AI Lock-In Is in Progress, and We Must Be Prepared

arXiv:2608.14565v1 Announce Type: new Abstract: AI safety research has mainly focused on two areas: technical alignment (ensuring AI systems produce human-aligned outputs) and the regulation of genera

safetyarxiv-cs-ai

Position: Certified Correctness in Neural Constraint Reasoning Requires Symbolic Integration

arXiv:2608.14569v1 Announce Type: new Abstract: Neural solvers for constraint satisfaction problems have achieved remarkable in-distribution accuracy, yet they suffer from a fundamental limitation per

agentsarxiv-cs-ai

Position: Evaluations of AI Moral Reasoning Still Miss Half of the Picture

arXiv:2608.14566v1 Announce Type: new Abstract: Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.e., whet

Position: Medical AI Neglects Real Treatment Outcomes

arXiv:2608.14598v1 Announce Type: new Abstract: Medical AI has rapidly improved its ability to perform diagnostic and prognostic tasks that lead to treatment decisions. But understanding of treatment

Position: Want Better ML Reviews? Stop Asking Nicely and Start Incentivizing with a Credit System

arXiv:2608.14571v1 Announce Type: new Abstract: With soaring submission counts, stricter reciprocal review policies, widespread adoption of platforms like OpenReview, and without the offsetting pressu

PosterText: Towards Unified Visual Text Generation and Editing for E-commerce Poster

arXiv:2608.16289v1 Announce Type: new Abstract: Automated e-commerce poster design requires both high-quality poster generation and flexible editing of existing designs. However, most existing methods

Pre-training Visual Dexterity in Simulation

arXiv:2608.15917v1 Announce Type: cross Abstract: Large-scale pre-training has made robot policy fine-tuning increasingly data-efficient, but this progress has largely been driven by datasets and embo

safetyarxiv-cs-ai

Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior

arXiv:2608.16323v1 Announce Type: cross Abstract: The spread of misinformation on social networks poses a significant challenge to online communities and society at large. Not all users contribute equ

researcharxiv-cs-lg

Prediction Inference of Time Series with Standard ReLU Deep Neural Networks

arXiv:2608.15362v1 Announce Type: cross Abstract: We propose a methodology based on the standard ReLU Deep Neural Networks (DNN) to make predictions and quantify their uncertainty. Classically, people

researcharxiv-cs-lg