All entries

Pedestrian-Aware LLM-Driven Behavioral Planning for Autonomous Vehicles

arXiv:2605.16858v1 Announce Type: cross Abstract: Autonomous Vehicles (AVs) must make reliable decisions in dense urban environments where pedestrian behavior is variable, sometimes abnormal, and ofte

Content type

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PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning

DGX agent

arXiv:2602.03352v2 Announce Type: replace Abstract: Reinforcement learning (RL) has shown strong promise for LLM-based machine translation, with recent methods such as GRPO demonstrating notable gains

model-releasesarxiv-cs-cl

19 May 2026

PEIRA: Learning Predictive Encoders through Inter-View Regressor Alignment

arXiv:2605.17671v1 Announce Type: cross Abstract: Non-contrastive self-supervised learning (SSL) is an effective framework for predictive representation learning, but popular (and in practice effectiv

People are generating over 1.5 billion images a week in ChatGPT. Researcher @kenjihata joins Product lead @adele__li and host @AndrewMayne t…

People are generating over 1.5 billion images a week in ChatGPT. Researcher @kenjihata joins Product lead @adele__li and host @AndrewMayne to explore the new use cases and trends emerging since the la

model-releasesopenai--x

Perception-based Image Denoising via Generative Compression

arXiv:2602.11553v2 Announce Type: replace-cross Abstract: Image denoising aims to remove noise while preserving structural details and perceptual realism, yet distortion-driven methods often produce o

Perceptual implications of automatic anonymization in pathological speech

arXiv:2505.00409v3 Announce Type: replace-cross Abstract: Automatic anonymization is increasingly used to enable ethical sharing of clinical speech, yet its perceptual and clinical consequences remain

Perfect Parallelization in Mini-Batch SGD with Classical Momentum Acceleration

model-releasesarxiv-cs-lg

arXiv:2605.18609v1 Announce Type: new Abstract: Accelerating stochastic gradient methods with classical momentum schemes, such as Polyak's heavy ball, has proven highly successful in training large-sc

PERL: Parameter Efficient Reasoning in CLIP Latent Space

model-releasesarxiv-cs-cv

arXiv:2605.18464v1 Announce Type: new Abstract: Contrastively trained vision-language models such as CLIP provide strong zero-shot transfer by aligning images and text in a shared embedding space. How

PERMA: Benchmarking Personalized Memory Agents via Event-Driven Preference and Realistic Task Environments

arXiv:2603.23231v2 Announce Type: replace Abstract: Empowering large language models with long-term memory is crucial for building agents that adapt to users' evolving needs. Existing evaluations of t

Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design

arXiv:2507.16307v2 Announce Type: replace-cross Abstract: Perovskite solar cells (PSCs) have rapidly emerged as a leading contender in next-generation photovoltaic technologies, owing to their excepti

applicationsarxiv-cs-ai

Agents

PersonaArena: Dynamic Simulation for Evaluating and Enhancing Persona-Level Role-Playing in Large Language Models

arXiv:2605.17044v1 Announce Type: new Abstract: Large language models (LLMs) increasingly serve as interactive social agents, yet their ability to maintain coherent and authentic persona-level role-pl

agentsarxiv-cs-ai

Tutorials

PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoning

arXiv:2601.08679v3 Announce Type: replace Abstract: As users increasingly expect LLMs to align with their preferences, personalized information becomes valuable. However, personalized information can

tutorialsarxiv-cs-ai

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited t…

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply pa

applicationskarpathy--x

PESD-TSF: A Period-Aware and Explicit Structured Decomposition Framework for Long-Term Time Series Forecasting

arXiv:2605.16449v1 Announce Type: cross Abstract: Deep forecasting models often suffer from attenuated periodic perception and entangled trend-noise representations as network depth increases. Moreove

PFlow-T: A Persistence-Driven Forward Process for Topology-Controlled Generation

arXiv:2605.17555v1 Announce Type: cross Abstract: Current topology aware diffusion models face an architectural mismatch by using Gaussian noise for corruption while recovering structural features thr

researcharxiv-cs-cv

PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamics

arXiv:2605.18303v1 Announce Type: cross Abstract: World models built on recurrent state space architectures enable efficient latent imagination, yet remain physically unstructured, producing dynamics

Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry

arXiv:2605.16325v1 Announce Type: cross Abstract: Phase-transition phenomena in deep learning (grokking, emergent capabilities, and ontological reorganization under context shift) have been studied th

Physics-Aligned Canonical Equivariant Fourier Neural Operator under Symmetry-Induced Shifts

arXiv:2605.18606v1 Announce Type: new Abstract: Neural operators approximate PDE solution maps, but they need not respect the symmetries of the governing equation. In out-of-distribution (OOD) regimes

safetyarxiv-cs-lg

Physics-Guided Geometric Diffusion for Macro Placement Generation

arXiv:2605.16451v1 Announce Type: cross Abstract: Macro placement is a pivotal stage in VLSI physical design, fundamentally determining the overall chip performance. Recent data-driven placement metho

PhysioSeq2Seq: A Hybrid Physiological Digital Twin and Sequence-to-Sequence LSTM for Long-Horizon Glucose Forecasting in Type 1 Diabetes

arXiv:2605.16860v1 Announce Type: cross Abstract: Accurate long-horizon glucose forecasting is critical for automated insulin delivery systems, which help people with type 1 diabetes (T1D) manage thei

Tutorials

PhysSkin: Real-Time and Generalizable Physics-Based Animation via Self-Supervised Neural Skinning

arXiv:2603.23194v2 Announce Type: replace-cross Abstract: Achieving real-time physics-based animation that generalizes across diverse 3D shapes and discretizations remains a fundamental challenge. We

tutorialsarxiv-cs-cv

PIMSM: Physics-Informed Multi-Scale Mamba for Stable Neural Representations under Distribution Shift

arXiv:2605.16351v1 Announce Type: cross Abstract: Scientific foundation models are expected to reuse representations under changes in dataset, acquisition protocol, and deployment domain, yet many seq

PIPER: Content-Based Table Search via profiling and LLM-Generated Pseudoqueries

arXiv:2605.18199v1 Announce Type: cross Abstract: The rapid growth of tabular datasets in data lakes, data spaces, and open data portals makes effective dataset search essential for reuse and analysis

PIXLRelight: Controllable Relighting via Intrinsic Conditioning

arXiv:2605.18735v1 Announce Type: new Abstract: We present PIXLRelight, a feed-forward approach for physically controllable single-image relighting. Existing methods either provide limited lighting co

researcharxiv-cs-cv

Local Ai

Plan First, Diffuse Later: Extrinsic Graph Guidance for Long-Horizon Diffusion Planning

arXiv:2605.16863v1 Announce Type: cross Abstract: Compositional diffusion models offer a promising route to long-horizon planning by denoising multiple overlapping sub-trajectories while ensuring that

local-aiarxiv-cs-ai

PlantPose: Universal Plant Skeleton Estimation via Tree-constrained Graph Generation

arXiv:2605.17773v1 Announce Type: new Abstract: Accurate estimation of plant skeletal structures (e.g., branching structures) from images is essential for smart agriculture and plant science. Unlike h

applicationsarxiv-cs-cv

Tutorials

PLATO Hand: Shaping Contact Behavior with Fingernails for Precise Manipulation

arXiv:2602.05156v2 Announce Type: replace Abstract: We present the PLATO Hand, a dexterous robotic hand with a hybrid fingertip that combines a rigid fingernail, embedded distal phalanx, and compliant

tutorialsarxiv-cs-ro

Tools

Playing around with AR libraries 😋🦋https://flybubbles.replit.app

This post showcases experimental work with augmented reality (AR) libraries, likely demonstrating interactive AR effects or visualizations built using web-based tools. The project appears to be a play

toolsreplit--x

Industry

Plex's 200% Lifetime Pass price hike tries forcing users to another subscription

Plex announced on May 19, 2026 that it is increasing the Lifetime Plex Pass price from 249.99 to 749.99, effective July 1, 2026 . This represents a 200% price increase and marks the second major price

industryars-technica

PluRule: A Benchmark for Moderating Pluralistic Communities on Social Media

arXiv:2605.17187v1 Announce Type: cross Abstract: Social media are shifting towards pluralism -- community-governed platforms where groups define their own norms. What violates rules in one community

Hardware

Pocket Foundation Models: Distilling TFMs into CPU-Ready Gradient-Boosted Trees

arXiv:2605.18654v1 Announce Type: cross Abstract: A fraud scorer needs to answer in under 2 ms. The best tabular foundation models (TFMs) take 151-1,275 ms on GPU. We close this gap by distilling the

hardwarearxiv-cs-ai

Pointwise Generalization in Deep Neural Networks

arXiv:2605.18598v1 Announce Type: new Abstract: We address the fundamental question of why deep neural networks generalize by establishing a pointwise generalization theory for fully connected network

safetyarxiv-cs-lg

Policy-Grounded Dynamic Facet Suggestions for Job Search

arXiv:2605.16479v1 Announce Type: cross Abstract: Job seekers often initiate search with short, underspecified queries. At LinkedIn, over 80% of job-related queries contain three or fewer keywords, ma

Policy Library CBF: Finite-Horizon Safety at Runtime via Parallel Rollouts

arXiv:2605.16588v1 Announce Type: new Abstract: Safety-critical autonomy in unstructured environments poses significant challenges for online safety certification under evolving constraints. We propos

safetyarxiv-cs-ro

Politicians who boost AI do not represent the views of their constituents. New polling in the UK shows: - Most people think AI will destroy …

Politicians who boost AI do not represent the views of their constituents. New polling in the UK shows: - Most people think AI will destroy more jobs than it creates (57% v 17%) - 7 in 10 are worried

safetygary-marcus--x

PopPy: Opportunistically Exploiting Parallelism in Python Compound AI Applications

arXiv:2605.18697v1 Announce Type: cross Abstract: Compound AI applications, which compose calls to ML models using a general-purpose programming language like Python, are widely used for a variety of

applicationsarxiv-cs-ai

Agents

PopuLoRA: Co-Evolving LLM Populations for Reasoning Self-Play

arXiv:2605.16727v1 Announce Type: new Abstract: We introduce PopuLoRA, a population-based asymmetric self-play framework for reinforcement learning with verifiable rewards (RLVR) post-training of LLMs

agentsarxiv-cs-ai

Position: A Three-Layer Probabilistic Assume-Guarantee Architecture Is Structurally Required for Safe LLM Agent Deployment

arXiv:2605.18672v1 Announce Type: new Abstract: This position paper argues that enforcing LLM agent safety within a single abstraction layer is not merely suboptimal but categorically insufficient for

Position: Age Estimation Models Do Not Process Biometric Data

arXiv:2605.17347v1 Announce Type: cross Abstract: When a neural network estimates someone's age from a photograph, does it process biometric data? The answer depends on whether identity-discriminative

safetyarxiv-cs-cv

Position: AI Evaluations Should be Grounded on a Theory of Capability

arXiv:2509.19590v2 Announce Type: replace Abstract: Evaluations of generative models are now ubiquitous, and their outcomes critically shape public and scientific expectations of AI's capabilities. Ye

Agents

Position: Universal Time Series Foundation Models Rest on a Category Error

arXiv:2602.05287v2 Announce Type: replace Abstract: This position paper argues that the pursuit of 'Universal Foundation Models for Time Series' rests on a fundamental category error, mistaking a stru

agentsarxiv-cs-ai

Position: Weight Space Should Be a First-Class Generative AI Modality

arXiv:2605.18632v1 Announce Type: cross Abstract: Neural network checkpoints have quietly become a large-scale data resource: millions of trained weight vectors now exist, each encoding task-, domain-

POST: Prior-Observation Adversarial Learning of Spatio-Temporal Associations for Multivariate Time Series Anomaly Detection

arXiv:2605.18128v1 Announce Type: new Abstract: Existing Multivariate Time Series Anomaly Detection (MTSAD) frameworks increasingly rely on integrating Graph Neural Networks (GNNs) with sequence model

Post-Trained MoE Can Skip Half Experts via Self-Distillation

arXiv:2605.18643v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) scales language models efficiently through sparse expert activation, and its dynamic variant further reduces computation by a

Local Ai

PPAI: Enabling Personalized LLM Agent Interoperability for Collaborative Edge Intelligence

arXiv:2605.18067v1 Announce Type: new Abstract: Deploying large language model (LLM) on edge device enables personalized LLM agents for various users. The growing availability of diverse personalized

local-aiarxiv-cs-cl

PQR: A Framework to Generate Diverse and Realistic User Queries that Elicit QA Agent Failures

arXiv:2605.16551v1 Announce Type: new Abstract: Evaluating LLM-based agents remains challenging because identifying meaningful failure cases often requires substantial human effort to design realistic

safetyarxiv-cs-cl

Preconditioned Norms: A Unified Framework for Steepest Descent, Quasi-Newton and Adaptive Methods

arXiv:2510.10777v3 Announce Type: replace Abstract: Optimization lies at the core of modern deep learning, yet existing methods often face a fundamental trade-off between adapting to problem geometry

researcharxiv-cs-lg

Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency

arXiv:2605.18732v1 Announce Type: cross Abstract: While scaling laws govern aggregate large language model performance, no scaling law has linked factual recall to both model size and training-data co