All entries

Katherine Hamilton / Wall Street Journal: OpenAI says its models now have more than 1B active users and are used by more than 2M businesses — The announcement comes after OpenAI said earlier this week

industrytechmeme

Model Releases

OpenAI’s entire growth loop: new models, price cuts, and Tibo’s token resets

DGX agent

OpenAI’s entire growth loop: new models, price cuts, and Tibo’s token resets major price cuts today: *80% drop for GPT-5.6 Luna, now 0.20 per million input tokens and 1.20 per million output *20% drop

model-releasesjerry-liu--x

31 Jul 2026

OPLD: On-Policy Latent Distillation for Multimodal Reasoning

arXiv:2607.28154v1 Announce Type: new Abstract: Interleaved multimodal Chain-of-Thought (CoT) improves visual reasoning by incorporating auxiliary visual evidence into intermediate reasoning. However,

safetyarxiv-cs-cv

Optimal Realistic Local AI for Most

model-releasesr-localllama

So you’ve got a 3090 or maybe even a 5090? Or more likely a 4060 8GB Ti. You wanna try local AI, you don’t know what it can/can’t do. 1) Install the best model you can. If you have a 3090 or a 5090, t

Optimizing production agents with Amazon Bedrock AgentCore Observability

As your AI agents move from prototype to production, the challenge shifts from getting them to work to keeping them fast and efficient. Learn how to use Amazon Bedrock AgentCore Observability and Amaz

agentsaws-ml-blog

Optimizing Regret

arXiv:2607.18866v2 Announce Type: replace-cross Abstract: Building on the identity that expected regret equals the covariance between costs and decisions, this paper develops a derivative theory of th

Optimizing Sensor Placement for Hydrogen Leak Detection in Enclosed Infrastructure: A Comparative Study Using CFD-informed Genetic Algorithm and DeepSets Neural Surrogate

arXiv:2607.26078v1 Announce Type: cross Abstract: Hydrogen infrastructure in enclosed environments, such as parking facilities for fuel cell vehicles, presents significant safety challenges due to hyd

safetyarxiv-cs-ai

Oracle-Budgeted Molecular Optimization with Short-Term Graph Memory

arXiv:2607.28437v1 Announce Type: new Abstract: Molecular optimization is commonly performed under a limited oracle budget, which makes deciding what to evaluate as important as deciding what to gener

ORCA-bench: How Ready Are Language Model Agents for Oncall?

model-releasesarxiv-cs-cl

arXiv:2607.28545v1 Announce Type: new Abstract: Large language models can write, patch, and search code, but oncall root cause analysis (RCA) demands something different: reasoning over noisy metrics,

OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models

model-releasesarxiv-cs-cl

arXiv:2607.28609v1 Announce Type: cross Abstract: Computer-using agents (CUAs) are advancing rapidly across the digital world. A CUA trajectory records the agent's actions, states, and reasoning. Veri

OVEarth-Bench: Evaluating Category Breadth and Query Diversity for Open-Vocabulary Earth Observation

arXiv:2607.27278v1 Announce Type: new Abstract: Open-vocabulary Earth observation (EO) aims to localize geospatial concepts specified in natural language rather than a fixed label set. Existing benchm

Oxide and Friends: The Open Weight Revolution with Simon Willison

model-releasessimon-willison

Oxide and Friends: The Open Weight Revolution with Simon Willison On Monday Bryan Cantrill and Adam Leventhal invited me to join their podcast to talk about the wild week we've had - with Kimi K3 show

PAC-MAN: Perception-Aware CBF-RL for Whole-Body Safety in Humanoid Dodgeball

model-releasesarxiv-cs-ro

arXiv:2607.28623v1 Announce Type: new Abstract: We present PAC-MAN, a perception-aware CBF-RL framework that couples control-barrier safety with deployment-realistic onboard sensing for whole-body hum

PanDent: Toward Comprehensive Tooth-Level Structure-Language Consistency in Dental Radiology

arXiv:2607.27378v1 Announce Type: new Abstract: Accurate evaluation of multimodal large language models (MLLMs) in dental panoramic radiography (orthopantomogram, OPG) is limited by the lack of fine-g

Industry

Papers and patents: Chinese military researchers distilled OpenAI and Anthropic models to train domestic AI systems and advance China's defense capabilities (Eduardo Baptista/Reuters)

Eduardo Baptista / Reuters: Papers and patents: Chinese military researchers distilled OpenAI and Anthropic models to train domestic AI systems and advance China's defense capabilities — Chinese milit

industrytechmeme

Partner Capability Estimation for Task-Agnostic Adaptation in Ad-Hoc Teamwork

arXiv:2607.27177v1 Announce Type: new Abstract: Effective collaboration with novel and diverse partners is a crucial skill for autonomous agents. Most current ad-hoc teamwork (AHT) approaches assume t

agentsarxiv-cs-ai

PCAP-LM: An LLM-Native Text Representation for TLS Bulk Traffic Analysis

model-releasesarxiv-cs-cl

arXiv:2607.28100v1 Announce Type: cross Abstract: Large language models (LLMs) offer powerful reasoning capabilities for network traffic analysis, but standard capture formats and their textual equiva

Period.

model-releasesfireworks-ai--x

Period. If LoRA is underperforming, don't reach for more expensive full parameter fine-tuning right away. We ran three cheap tests (data coverage, optimization, rank) to see if we could close the gap

Persistent Gaussian Perturbations Prevent Oversmoothing in Recurrent Graph Neural Networks

arXiv:2607.28185v1 Announce Type: new Abstract: Oversmoothing is a fundamental limitation of deep graph neural networks (GNNs), where repeated message passing causes node representations to become inc

Tutorials

PhiZero: A World Model Built Around Physical Language

arXiv:2607.28624v1 Announce Type: new Abstract: We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing phys

tutorialsarxiv-cs-cv

Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration

arXiv:2408.04227v2 Announce Type: replace-cross Abstract: Infrared imaging and turbulence strength measurements are in widespread demand in many fields. This paper introduces a Physical Prior Guided C

PlantBGC: Transformer for Plant BGC Discovery via Label-Free Domain Adaptation and Weak Supervision

arXiv:2607.27258v1 Announce Type: cross Abstract: Plant biosynthetic gene clusters (BGCs) encode specialized-metabolite pathways, yet curated plant BGC labels remain scarce, hindering supervised disco

PlatformBid: An Auto-Bidding Benchmark from a Unified Advertising Platform's Perspective

arXiv:2607.27265v1 Announce Type: new Abstract: Real-time bidding is central to computational advertising, comprising three elements: Supply Side Platform (SSP) selling ad impressions, Demand Side Pla

Policy Gradient Steering: Interventions from Behavioral Objectives

arXiv:2607.27574v1 Announce Type: new Abstract: Activation steering has emerged in large language models as a lightweight alternative for dynamically changing a model's behavior at inference time. How

PoseMaster: A Unified 3D Native Framework for Stylized Pose Generation

arXiv:2506.21076v4 Announce Type: replace Abstract: Pose stylization, which aims to synthesize stylized content aligning with target poses, serves as a fundamental task across 2D, 3D, and video domain

safetyarxiv-cs-cv

Position, Not Provenance: Separating Reasoning Mediation from Sycophancy in Medical Vision-Language Models

arXiv:2607.27304v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) generate chain-of-thought (CoT) reasoning before answering clinical questions, but whether this reasoning causal

Pramana: A Composable, Domain-Specific Backend for Empirical Networking Research

arXiv:2607.26352v1 Announce Type: cross Abstract: Networking research advances by turning hypotheses into empirical evidence, so accelerating it means reducing the lag between ideation (synthesizing a

agentsarxiv-cs-ai

Predict before you train: Scaling Laws for particle physics foundation models

arXiv:2607.23377v1 Announce Type: cross Abstract: The largest machine learning models in particle physics are also the most expensive to train, yet the return on scaling a given architecture cannot be

researcharxiv-cs-ai

PrintAnything: Learning an Intermediate Representation for 3D printing G-code Generation

arXiv:2607.27729v1 Announce Type: new Abstract: Point clouds are one of the most fundamental and widely used 3D representations, serving as the most basic geometric representation of 3D shapes. Nevert

Private Face Recognition Training Dataset Publication via Identity-Decoupled and Geometry-Preserving Face Distillation

arXiv:2607.27764v1 Announce Type: new Abstract: Publishing private face recognition~(FR) training datasets is privacy-sensitive because faces expose identity information. Private FR training dataset p

Procedural Fairness in Multi-Agent Bandits

arXiv:2601.10600v2 Announce Type: replace-cross Abstract: In the context of multi-agent multi-armed bandits (MA-MAB), fairness is often reduced to outcomes: maximizing welfare, reducing inequality, or

ProgFormer: Hierarchical Voxel Diffusion Transformer for Longitudinal Brain MRI Prediction

arXiv:2607.27537v1 Announce Type: new Abstract: Predicting future structural MRI of a brain is challenging because longitudinal changes are often subtle and confined to specific anatomical regions, wh

Applications

Prompt Chaining in Practice: A Case Study in Automated Scholarly Report Generation

arXiv:2607.27210v1 Announce Type: new Abstract: The exponential growth of scholarly publications requires automated tools for effective information synthesis. However, simple, single-shot prompting me

applicationsarxiv-cs-cl

Industry

Prompts for a black-and-white editorial headshot

After trying several AI headshot apps, I decided that they all suck. I've always liked Marco Grob's TIME cover portraits so I've been refining some prompts to generate these types of headshots. Both b

industryr-chatgpt

Property-driven Causal Abstractions for Markov Decision Processes

arXiv:2607.26787v1 Announce Type: new Abstract: Markov Decision Processes (MDPs) are widely used as decision-making models, commonly specified over factored state spaces through state variables and th

researcharxiv-cs-ai

Prox: Training-Free FFN Activation Sparsity via Approximate Intermediate-Channel Salience in LLMs

arXiv:2607.27591v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) dominate memory traffic and computation in large language model (LLM) inference, making them a primary target for activat

researcharxiv-cs-cl

Psych-ECA: A Reproducible Semi-Synthetic Benchmark for Synthetic Control Arms in Longitudinal Psychiatry

arXiv:2607.27224v1 Announce Type: cross Abstract: External and synthetic control arms (ECAs) are entering psychiatric drug development, but the field lacks a benchmark that evaluates the properties re

PUDA: An AI-Native Hardware Harness for Self-Driving Laboratories

arXiv:2607.26464v1 Announce Type: cross Abstract: Physical Unified Device Architecture (PUDA) is an AI-native hardware harness for self-driving laboratories (SDLs). Rather than building a human-center

agentsarxiv-cs-ai

Pushing the Frontier on Approximate EFX Allocations

arXiv:2406.12413v3 Announce Type: replace-cross Abstract: We study the problem of allocating a set of indivisible goods to a set of agents with additive valuation functions, aiming to achieve approxim

researcharxiv-cs-ai

QAdapt: A Noise-Adaptive Neural Pre-Decoding Framework for Quantum Error Correction

arXiv:2607.28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale. In pra

QQWorld: Quantile-Quantile Matching for World Model Regularization

arXiv:2607.28415v1 Announce Type: cross Abstract: Latent world models enable efficient planning by predicting future states in a compact representation space, but their performance depends critically

safetyarxiv-cs-cv

Quadratic Objective Perturbation: Curvature-Based Differential Privacy

arXiv:2605.05905v2 Announce Type: replace Abstract: Objective perturbation is a standard mechanism in differentially private empirical risk minimization. In particular, Linear Objective Perturbation (

QuantWAMs: Calibrating at the Right Granularity for World Action Models

arXiv:2607.28405v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly predict future observations and actions, but their iterative denoising and closed-loop execution make efficient dep

Qwen-UI-Agent Technical Report: Toward Next-Generation Real-World Centric Foundation GUI Agents

arXiv:2607.28227v1 Announce Type: cross Abstract: GUI agents have the potential to become a general purpose executor over existing digital devices. To advance them toward real-world use, we envision a

RadHarmony: Radiological Data Handling in the Era of Agentic AI

arXiv:2607.27235v1 Announce Type: cross Abstract: Training deep learning models on radiological images requires integrating heterogeneous datasets across different sources, file formats, directory lay

agentsarxiv-cs-cv

RaDiVe: Robust 4D Radar Odometry with Distance-Bounded NDT and Velocity-Discrepancy Point Uncertainty

arXiv:2607.28045v1 Announce Type: new Abstract: Recent advances in 4D radar enable robust perception in adverse weather; however, the inherent sparsity, noise, and limited positional precision of rada

researcharxiv-cs-ro

Random Projection Flows for Efficient Manifold Density Estimation

arXiv:2509.25228v3 Announce Type: replace Abstract: Accurate density estimation is crucial for understanding complex high-dimensional data, but it becomes challenging when the data lies on or near low

Real-Time Hard Peak Age-of-Information Safety with No-Regret Learning

arXiv:2607.27626v1 Announce Type: new Abstract: Safety-critical IoT systems such as industrial closed-loop control, V2X coordination, and remote teleoperation require every sensor's peak Age of Inform