All entries

Pioneering AI-assisted code migration: How Google achieved 6x faster migration from TensorFlow to JAX

model-releasesgoogle-cloud-ai

AI coding agents are rapidly becoming ubiquitous across the software industry, fundamentally changing how developers write, test, and debug daily code. While these tools excel at localized, self-conta

Model Releases

PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolution

DGX agent

arXiv:2605.03399v1 Announce Type: new Abstract: Probabilistic super-resolution of high-dimensional spatial fields using diffusion models is often computationally prohibitive due to the cost of operati

model-releasesarxiv-cs-lg

6 May 2026

Poly-EPO: Training Exploratory Reasoning Models

arXiv:2604.17654v3 Announce Type: replace Abstract: Exploration is a cornerstone of learning from experience: it enables agents to find solutions to complex problems, generalize to novel ones, and sca

safetyarxiv-cs-ai

Population-Aware Imitation Learning in Mean-field Games with Common Noise

arXiv:2605.03357v1 Announce Type: new Abstract: Mean Field Games (MFGs) provide a powerful framework for modeling the collective behavior of large populations of interacting agents. In this paper, we

Pose Tracking with a Foundation Pose Model and an Ensemble Directional Kalman Filter

arXiv:2605.03105v1 Announce Type: new Abstract: This paper introduces the ensemble directional Kalman filter (EnDKF), an ensemble-based Kalman filtering approach for pose tracking that jointly estimat

Position: How can Graphs Help Large Language Models?

arXiv:2605.02452v1 Announce Type: new Abstract: With the rapid advancement of large language models (LLMs), classic graph learning tasks have greatly benefited from LLMs, including improved encoding o

researcharxiv-cs-ai

Position: LLM Serving Needs Mathematical Optimization and Algorithmic Foundations, Not Just Heuristics

arXiv:2605.01280v1 Announce Type: cross Abstract: This position paper argues that LLM inference serving has outgrown generic heuristics and now demands mathematical optimization and algorithmic founda

researcharxiv-cs-ai

Position: Safety and Fairness in Agentic AI Depend on Interaction Topology, Not on Model Scale or Alignment

arXiv:2605.01147v1 Announce Type: new Abstract: As large language models are increasingly deployed as interacting agents in high-stakes decisions, the AI safety community assumes that safety propertie

safetyarxiv-cs-ai

(POSTER) From Sensors to Insight: Rapid, Edge-to-Core Application Development for Sensor-Driven Applications

arXiv:2605.02844v1 Announce Type: cross Abstract: Scientists increasingly rely on sensor-based data; however transforming raw streams into insights across the edge-to-cloud continuum remains difficult

researcharxiv-cs-ai

Posterior-First Neural PDE Simulation: Inferring Hidden Problem State from a Single Field

arXiv:2605.03247v1 Announce Type: new Abstract: Neural PDE simulators often receive only a single observed field at deployment. In this setting, a field-to-future predictor can collapse distinct laten

Power-Softmax: Towards Secure LLM Inference over Encrypted Data

arXiv:2410.09457v2 Announce Type: replace Abstract: Modern cryptographic methods for implementing privacy-preserving LLMs such as gls{HE} require the LLMs to have a polynomial form. Forming such a rep

@PPLXfinance @PPLXDevs On FinSearchComp T1, Finance Search delivered the highest accuracy for live financial data and the lowest cost per co…

applicationsperplexity--x

@PPLXfinance @PPLXDevs On FinSearchComp T1, Finance Search delivered the highest accuracy for live financial data and the lowest cost per correct answer in the cohort. Every result includes citations,

Practical Limits of Autonomous Test Repair: A Multi-Agent Case Study with LLM-Driven Discovery and Self-Correction

arXiv:2605.01471v1 Announce Type: cross Abstract: Maintaining reliable UI test suites in large-scale enterprise applications is a persistent and costly challenge. We present an industrial case study o

agentsarxiv-cs-ai

Precisely what I have been saying since day 1: the challenge in generative AI is reliability. That was the challenge, and still is.

applicationsgary-marcus--x

Precisely what I have been saying since day 1: the challenge in generative AI is reliability. That was the challenge, and still is. AI pretenders vs. AI contenders. It's those who still haven’t realiz

Predicting Euler Characteristics and Constructing Topological Structure Using Machine Learning Techniques

arXiv:2605.02947v1 Announce Type: new Abstract: This study proposes a novel approach to extract topological properties, specifically the Euler characteristic, from input images using neural networks w

Predicting missing values: A good idea?

arXiv:2605.03733v1 Announce Type: cross Abstract: Minimizing the Mean Squared Error (MSE) is a key objective in machine learning and is commonly used for imputing missing values. While this approach p

Prediction horizon shapes representations in predictive learning

arXiv:2511.09290v2 Announce Type: replace Abstract: Predictive learning has emerged as a central paradigm for training models across diverse data domains and is increasingly viewed as a foundation for

Tutorials

Preemptive Solving of Future Problems: Multitask Preplay in Humans and Machines

arXiv:2507.05561v2 Announce Type: replace Abstract: Humans can pursue a near-infinite variety of tasks, but typically can only pursue a small number at the same time. We hypothesize that humans levera

tutorialsarxiv-cs-lg

President Biden made health insurance more affordable for millions of Americans in the ACA marketplace. The Republicans’ actions increased p…

President Biden made health insurance more affordable for millions of Americans in the ACA marketplace. The Republicans’ actions increased prices by 58% on average—amounting to huge extra costs for th

researchyann-lecun--x

Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs

arXiv:2605.03964v1 Announce Type: new Abstract: Training machine learning interatomic potentials (MLIPs) for reactive chemistry is often bottlenecked by the high cost of quantum chemical labels and th

Preview in Claude Code on desktop makes it easy to give Claude context. You can attach DOM elements or use the pencil tool to draw directly …

Claude Code on desktop includes a preview feature that allows users to provide context to Claude by attaching DOM elements or drawing directly with a pencil tool. This functionality streamlines the pr

model-releasesthariq--x

Previously this feature was only available to Replit Pro and Enterprise users. We are expanding this to Replit Starter and Core tier users a…

Replit has expanded a previously premium feature to its lower-tier users, making it available to Starter and Core tier subscribers in addition to Pro and Enterprise users. This expansion democratizes

applicationsreplit--x

PriorNet: Prior-Guided Engagement Estimation from Face Video

arXiv:2605.03615v1 Announce Type: new Abstract: Engagement estimation from face video remains challenging because facial evidence is often incomplete, labeled data are limited, and engagement annotati

Tutorials

PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL

arXiv:2605.02917v1 Announce Type: new Abstract: Supervised deep learning models for automated CTG analysis are typically constrained by narrowly curated labelled datasets and limited patient cohorts,

tutorialsarxiv-cs-lg

Prism: Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models

model-releasesarxiv-cs-lg

arXiv:2602.01842v3 Announce Type: replace Abstract: Inference-time compute has re-emerged as a practical way to improve LLM reasoning. Most test-time scaling (TTS) algorithms rely on autoregressive de

PrismAgent: Illuminating Harm in Memes via a Zero-Shot Interpretable Multi-Agent Framework

arXiv:2605.02940v1 Announce Type: new Abstract: The rapid spread of memes makes harmful content detection increasingly crucial, as effective identification can curb the circulation of misinformation.

agentsarxiv-cs-lg

Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning

arXiv:2605.02372v1 Announce Type: cross Abstract: The growing development of artificial intelligence based solutions, together with privacy legislation, has driven the rise of the so-called privacy pr

safetyarxiv-cs-ai

PROBE: Probabilistic Occupancy BEV Encoding with Analytical Translation Robustness for 3D Place Recognition

arXiv:2603.05965v2 Announce Type: replace-cross Abstract: We present PROBE (PRobabilistic Occupancy BEV Encoding), a learning-free LiDAR place recognition descriptor that models each BEV cell's occupa

Proteo-R1: Reasoning Foundation Models for De Novo Protein Design

arXiv:2605.02937v1 Announce Type: new Abstract: Deep learning in de novo protein design has achieved atomic-level fidelity. However, existing models remain largely non-deliberative: they directly synt

Provable Accuracy Collapse in Embedding-Based Representations under Dimensionality Mismatch

arXiv:2605.03346v1 Announce Type: cross Abstract: Embedding-based representations in Euclidean space R^d are a cornerstone of modern machine learning, where a major goal is to use the smallest dimensi

Pseudo-differential-enhanced physics-informed neural networks

arXiv:2602.14663v2 Announce Type: replace Abstract: We present pseudo-differential enhanced physics-informed neural networks (PINNs), an extension of gradient enhancement but in Fourier space. Gradien

psifx -- Psychological and Social Interactions Feature Extraction Package

arXiv:2407.10266v5 Announce Type: replace Abstract: psifx is a plug-and-play multi-modal feature extraction toolkit, aiming to facilitate and democratize the use of state-of-the-art machine learning t

researcharxiv-cs-cl

Quality-Aware Exploration Budget Allocation for Cooperative Multi-Agent Reinforcement Learning

arXiv:2605.01865v1 Announce Type: cross Abstract: Cooperative multi-agent reinforcement learning (MARL) requires agents to discover joint strategies in a combinatorially large state-action space, yet

agentsarxiv-cs-ai

Quantifying the human visual exposome with vision language models

arXiv:2605.03863v1 Announce Type: cross Abstract: The visual environment is a fundamental yet unquantified determinant of mental health. While the concept of the environmental exposome is well establi

agentsarxiv-cs-cv

Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits

model-releasesarxiv-cs-lg

arXiv:2605.03434v1 Announce Type: new Abstract: Reinforcement learning is one of the most challenging learning paradigms where efficacy and efficiency gains are extremely valuable. Hierarchical reinfo

Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution

arXiv:2505.00334v3 Announce Type: replace Abstract: Image Super-Resolution is a fundamental problem in computer vision with broad applications spacing from medical imaging to satellite analysis. The a

researcharxiv-cs-cv

RAG over Thinking Traces Can Improve Reasoning Tasks

model-releasesarxiv-cs-cl

arXiv:2605.03344v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) has proven effective for knowledge-intensive tasks, but is widely believed to offer limited benefit for reasoning

Raising the Ceiling: Better Empirical Fixation Densities for Saliency Benchmarking

arXiv:2605.03885v1 Announce Type: new Abstract: Empirical fixation densities, spatial distributions estimated from human eye-tracking data, are foundational to saliency benchmarking. They directly sha

Random test functions, H^{-1} norm equivalence, and stochastic variational physics-informed neural networks

arXiv:2605.03542v1 Announce Type: cross Abstract: The dual norm characterisation of weak solutions of second-order linear elliptic partial differential equations is mathematically natural but computat

Rational Communication Shapes Morphological Composition

arXiv:2605.03510v1 Announce Type: new Abstract: Human languages expand vocabularies by combining existing morphemes rather than inventing arbitrary forms. Communicative efficiency shapes lexical syste

applicationsarxiv-cs-cl

RD-ViT: Recurrent-Depth Vision Transformer for Semantic Segmentation with Reduced Data Dependence Extending the Recurrent-Depth Transformer Architecture to Dense Prediction

arXiv:2605.03999v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve state-of-the-art segmentation accuracy but require large training datasets because each layer has unique parameters t

Re-Key-Free, Risky-Free: Adaptable Model Usage Control

arXiv:2511.18772v2 Announce Type: replace-cross Abstract: Deep neural networks (DNNs) have become valuable intellectual property of model owners, due to the substantial resources required for their de

applicationsarxiv-cs-ai

Real Image Denoising with Knowledge Distillation for High-Performance Mobile NPUs

arXiv:2605.03680v1 Announce Type: new Abstract: While deep-learning-based image restoration has achieved unprecedented fidelity, deployment on mobile Neural Processing Units (NPUs) remains bottlenecke

Realizable Bayes-Consistency for General Metric Losses

arXiv:2605.03823v1 Announce Type: new Abstract: We study strong universal Bayes-consistency in the realizable setting for learning with general metric losses, extending classical characterizations bey

really cool work by the Harvey team, excited to partner with them to push forward research on designing + understanding agents across Long H…

applicationsharrison-chase--x

really cool work by the Harvey team, excited to partner with them to push forward research on designing + understanding agents across Long Horizon Legal work the first peak I got at LAB was 'woah this

Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models

arXiv:2605.02912v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) has traditionally been framed as binary classification or outlier detection, providing neither interpretable reasoning nor

researcharxiv-cs-cv

Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction

model-releasesarxiv-cs-ai

arXiv:2509.12464v2 Announce Type: replace Abstract: Reasoning language models such as DeepSeek-R1 produce long chain-of-thought traces during inference time which make them costly to deploy at scale.

ReCode: Reinforcing Code Generation with Reasoning-Process Rewards

model-releasesarxiv-cs-cl

arXiv:2508.05170v3 Announce Type: replace-cross Abstract: In practice, rigorous reasoning is often a key driver of correct code, while Reinforcement Learning (RL) for code generation often neglects op