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Preserving Disagreement: Architectural Heterogeneity and Coherence Validation in Multi-Agent Policy Simulation

arXiv:2604.26561v1 Announce Type: cross Abstract: Multi-agent deliberation systems using large language models (LLMs) are increasingly proposed for policy simulation, yet they suffer from artificial c

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Agents

Principled Learning-to-Communicate with Quasi-Classical Information Structures

DGX agent

arXiv:2603.03664v2 Announce Type: replace-cross Abstract: Learning-to-communicate (LTC) in partially observable environments has received increasing attention in deep multi-agent reinforcement learnin

agentsarxiv-cs-lg

30 Apr 2026

Privacy-Preserving Clothing Classification using Vision Transformer for Thermal Comfort Estimation

arXiv:2604.26184v1 Announce Type: new Abstract: A privacy-preserving clothing classification scheme is presented to enable secure occupant-centric control (OCC) systems. Although the utilization of ca

Local Ai

Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization

arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process modeling difficult. Fed

local-aiarxiv-cs-ai

Probabilistic data quality assessment for structural monitoring data via outlier-resistant conditional diffusion model

arXiv:2604.26366v1 Announce Type: cross Abstract: Data quality assessment is an essential step that ensures the reliability of the subsequent structural health monitoring (SHM) tasks. This study propo

applicationsarxiv-cs-lg

Safety

Probe-then-Plan: Environment-Aware Planning for Industrial E-commerce Search

arXiv:2603.15262v2 Announce Type: replace Abstract: Modern e-commerce search is evolving to resolve complex user intents. While Large Language Models (LLMs) offer strong reasoning, existing LLM-based

safetyarxiv-cs-ai

ProcFunc: Function-Oriented Abstractions for Procedural 3D Generation in Python

arXiv:2604.26943v1 Announce Type: new Abstract: We introduce ProcFunc, a library for Blender-based procedural 3D generation in Python. ProcFunc provides a library of easy-to-use Python functions, whic

Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models

arXiv:2604.26508v1 Announce Type: cross Abstract: Deploying Vision-Language Models (VLMs) on edge devices remains challenging due to their substantial computational and memory demands, which exceed th

Prompt templates as configs, not code

This post was written in April 2026. Cloud products, feature maturity, and recommended patterns change over time, so readers should treat these examples as directional guidance. For teams already usin

applicationsarize-ai

Tutorials

PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Space

arXiv:2604.06061v2 Announce Type: replace Abstract: Text-to-image generation has progressed rapidly, but faithfully generating complex scenes requires extensive trial-and-error to find the exact promp

tutorialsarxiv-cs-lg

Local Ai

Provable Coordination for LLM Agents via Message Sequence Charts

arXiv:2604.17612v2 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are difficult to reason about. Coordination errors such as deadlocks or type-mismatc

local-aiarxiv-cs-ai

q3-MuPa: Quick, Quiet, Quantitative Multi-Parametric MRI using Physics-Informed Diffusion Models

arXiv:2512.23726v2 Announce Type: replace-cross Abstract: The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enable

QERNEL: a Scalable Large Electron Model

arXiv:2604.26018v1 Announce Type: cross Abstract: We introduce QERNEL, a foundational neural wavefunction that variationally solves families of parameterized many-electron Hamiltonians and captures th

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch

arXiv:2604.26505v1 Announce Type: cross Abstract: Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static qu

researcharxiv-cs-lg

Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model

arXiv:2412.11399v4 Announce Type: replace Abstract: Driven by global climate change and the ongoing energy transition, the coupling between power supply capabilities and meteorological factors has bec

researcharxiv-cs-lg

Quantum Feature Selection with Higher-Order Binary Optimization on Trapped-Ion Hardware

model-releasesarxiv-cs-lg

arXiv:2604.26834v1 Announce Type: cross Abstract: We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorpor

Quantum Gatekeeper: Multi-Factor Context-Bound Image Steganography with VQC Based Key Derivation on Quantum Hardware

arXiv:2604.26413v1 Announce Type: cross Abstract: This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic

Quoting Andrew Kelley

It's a common misconception that we can't tell who is using LLM and who is not. I'm sure we didn't catch 100% of LLM-assisted PRs over the past few months, but the kind of mistakes humans make are fun

agentssimon-willison

Qvine: Vine Structured Quantum Circuits for Loading High Dimensional Distributions

arXiv:2604.26213v1 Announce Type: cross Abstract: Loading high dimensional distributions is an important task for utilizing quantum computers on applications ranging from machine learning to finance.

applicationsarxiv-cs-ai

QYOLO: Lightweight Object Detection via Quantum Inspired Shared Channel Mixing

arXiv:2604.26435v1 Announce Type: cross Abstract: The rapid advancement of object detection architectures has positioned single stage detectors as the dominant solution for real-time visual perception

[R] Joint Embedding Variational Bayes (TMLR ’26)

researchr-machinelearning

Variational Joint Embedding (VJE) is a framework that synthesizes joint embedding and variational inference to enable self-supervised learning of probabilistic representations in a reconstruction-free

Safety

R2RGEN: Real-to-Real 3D Data Generation for Spatially Generalized Manipulation

arXiv:2510.08547v2 Announce Type: replace-cross Abstract: Towards the aim of generalized robotic manipulation, spatial generalization is the most fundamental capability that requires the policy to wor

safetyarxiv-cs-cv

RADIO-ViPE: Online Tightly Coupled Multi-Modal Fusion for Open-Vocabulary Semantic SLAM in Dynamic Environments

model-releasesarxiv-cs-cv

arXiv:2604.26067v1 Announce Type: new Abstract: We present RADIO-ViPE (Reduce All Domains Into One -- Video Pose Engine), an online semantic SLAM system that enables geometry-aware open-vocabulary gro

RaMP: Runtime-Aware Megakernel Polymorphism for Mixture-of-Experts

arXiv:2604.26039v1 Announce Type: cross Abstract: The optimal kernel configuration for Mixture-of-Experts (MoE) inference depends on both batch size and the expert routing distribution, yet production

Random Cloud: Finding Minimal Neural Architectures Without Training

arXiv:2604.26830v1 Announce Type: cross Abstract: I propose the Random Cloud method, a training-free approach to neural architecture search that discovers minimal feedforward network topologies throug

RE-MCDF: Closed-Loop Multi-Expert LLM Reasoning for Knowledge-Grounded Clinical Diagnosis

arXiv:2602.01297v3 Announce Type: replace Abstract: Electronic medical records (EMRs), particularly in neurology, are inherently heterogeneous, sparse, and noisy, which poses significant challenges fo

agentsarxiv-cs-ai

Reactive Motion Generation via Phase-varying Neural Potential Functions

arXiv:2604.26450v1 Announce Type: new Abstract: Dynamical systems (DS) methods for Learning-from-Demonstration (LfD) provide stable, continuous policies from few demonstrations. First-order dynamical

researcharxiv-cs-ro

Read the full case study: https://devin.ai/customers/evinova

applicationscognition-ai--x

Evinova is a customer case study from Cognition AI showcasing how their Devin AI platform was applied to solve real-world development challenges. The case study likely demonstrates specific productivi

Real-time Global Illumination for Dynamic 3D Gaussian Scenes

arXiv:2503.17897v2 Announce Type: replace-cross Abstract: We present a real-time global illumination approach along with a pipeline for dynamic 3D Gaussian models and meshes. Building on a formulated

Reasoning Gets Harder for LLMs Inside A Dialogue

model-releasesarxiv-cs-cl

arXiv:2603.20133v2 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance on many reasoning benchmarks, yet these evaluations typically focus on isolated tasks that d

Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies

arXiv:2604.26903v1 Announce Type: cross Abstract: This paper provides a concise yet comprehensive review of recent advancements in millimeter-wave (mm-wave) oscillators below 100 GHz and sub-terahertz

Safety

Recipes for Calibration Checks in Safety-Critical Applications

arXiv:2604.26479v1 Announce Type: cross Abstract: Safety-critical prediction systems, such as autonomous vehicles, weather forecasters, and medical monitors, commonly rely on probabilistic forecasters

safetyarxiv-cs-lg

Recurrence-Based Nonlinear Vocal Dynamics as Digital Biomarkers for Depression Detection from Conversational Speech

arXiv:2604.26242v1 Announce Type: cross Abstract: Digital biomarkers for depression have largely relied on static acoustic descriptors, pooled summary statistics, or conventional machine learning repr

researcharxiv-cs-lg

Industry

Red Hat redefines the Kubernetes control plane for AI

The recent KubeCon + CloudNativeCon Europe event did not read like a celebration so much as an admission. AI is everywhere, but the systems underneath it are strained — not by models, but by layout. T

industrysiliconangle

Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale

researchmicrosoft-research

Safe agents don’t guarantee a safe ecosystem of interconnected agents. Microsoft Research examines what breaks when AI agents interact and why network-level risks require new approaches. The post Red-

Industry

Reddit reports Q1 revenue up 69% YoY to 663M vs. 611M est., DAUq up 17% to 126.8M, above est., forecasts Q2 revenue above est.; RDDT jumps 13%+ after hours (Jonathan Vanian/CNBC)

Jonathan Vanian / CNBC: Reddit reports Q1 revenue up 69% YoY to 663M vs. 611M est., DAUq up 17% to 126.8M, above est., forecasts Q2 revenue above est.; RDDT jumps 13%+ after hours — Reddit reported be

industrytechmeme

ReGATE: Learning Faster and Better with Fewer Tokens in MLLMs

arXiv:2507.21420v3 Announce Type: replace-cross Abstract: The computational cost of training multimodal large language models (MLLMs) grows rapidly with the number of processed tokens. Existing effici

researcharxiv-cs-cl

ReLoop: Structured Modeling and Behavioral Verification for Reliable LLM-Based Optimization

arXiv:2602.15983v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can translate natural language into optimization code, but silent failures pose a critical risk: code that execut

Replit is turning 10, and we are making Agent free Get ready to have fun building! Want prizes? Join our buildathon in partnership with Anth…

Replit announced its 10th anniversary milestone and is making their Agent product free to users. The company is hosting a buildathon partnership event with Anthropic and offering prizes to encourage d

agentsreplit--x

🎂 Replit turns 10 this weekend, and we're giving every Replit user free Agent for 24 hours on Saturday.🤯 Clear your Saturday. And tune in …

🎂 Replit turns 10 this weekend, and we're giving every Replit user free Agent for 24 hours on Saturday.🤯 Clear your Saturday. And tune in live tomorrow, Friday at 9 AM PT, when we go live to walk you

agentsreplit--x

Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding

arXiv:2604.26031v1 Announce Type: new Abstract: This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challen

Industry

Researchers try to cut the genetic code from 20 to 19 amino acids

Scientists have reengineered bacteria to run a core part of their cellular machinery with just 19 amino acids instead of the standard 20 , focusing on eliminating isoleucine through AI-guided protein

industryars-technica

resharing this note, find it helpful given all the great open evals work + teams building vertical agents Evals are a proxy for the behavior…

model-releasesharrison-chase--x

resharing this note, find it helpful given all the great open evals work + teams building vertical agents Evals are a proxy for the behavior we want our agent to exhibit in production Model+Harness pu

Resume-ing Control: (Mis)Perceptions of Agency Around GenAI Use in Recruiting Workflows

arXiv:2604.26851v1 Announce Type: cross Abstract: When generative AI (genAI) systems are used in high-stakes decision-making, its recommended role is to aid, rather than replace, human decision-making

Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective

arXiv:2604.25975v1 Announce Type: cross Abstract: Key-value (KV) caching is essential for large language model inference, yet its memory overhead poses a critical bottleneck for long-context generatio

Rethinking the Harmonic Loss via Non-Euclidean Distance Layers

arXiv:2603.10225v3 Announce Type: replace-cross Abstract: Cross-entropy loss has long been the standard choice for training deep neural networks, yet it suffers from interpretability limitations, unbo

Retrieval-Augmented LLMs for Evidence Localization in Clinical Trial Recruitment from Longitudinal EHR Narratives

arXiv:2604.05190v2 Announce Type: replace-cross Abstract: Screening patients for enrollment is a well-known, labor-intensive bottleneck that leads to under-enrollment and, ultimately, trial failures.

RetroMotion: Retrocausal Motion Forecasting Models are Instructable

arXiv:2505.20414v2 Announce Type: replace-cross Abstract: Motion forecasts of road users (i.e., agents) vary in complexity depending on the number of agents, scene constraints, and interactions. In pa

agentsarxiv-cs-ai