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Artificial Intelligence / Machine Learning · 5

Automation / Agentic Systems · 5

Research Papers · 2

Embedded Systems · 5

Computer Systems · 4

Developer Tools / Open Source · 5

Cloud / Infrastructure · 1

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv6/26/2026
Recently

PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception

We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness. Shifting evaluation from holistic semantic matching to rigorous atomic auditing, PerceptionRubrics pairs 1,038 information-dense images with over 12,000 instance-specific rubrics. These criteria are derived from golden captions constructed via a novel Circular Peer-Review consensus pipeline and then distilled into a dual-stream system of Must-Right (essential facts) and Easy-Wrong (fine-grained details) rubrics. Authors: Yana Wei, Hongbo Peng, Yanlin Lai.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
arXiv6/26/2026
Recently

VGB for Masked Diffusion Model: Efficient Test-time Scaling for Reward Satisfaction and Sample Editing

Inference-time scaling is a promising paradigm to improve generative models, especially when outputs must satisfy structural constraints or optimize downstream rewards. We consider Masked Diffusion Model (MDM) and introduce MDM-VGB, a discrete diffusion sampler that augments unmasking generation with theoretically principled reward-guided remasking. Inspired by the recent success of the classical Jerrum-Sinclair backtracking Markov chain in reward-tilted generation, MDM-VGB extends the backtracking random walk from a fixed prefix tree to a masked-state graph, allowing tokens to be unmasked and remasked at arbitrary positions. Authors: Kijung Jeon, Thuy-Duong Vuong, Molei Tao.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Inference-time scaling is a promising paradigm to improve generative models, especially when outputs must satisfy structural constraints or optimize downstream rewards.

Primary paperarxivcs.LG
Original
Artificial Intelligence / Machine Learning
arXiv6/26/2026
Recently

Towards Automating Scientific Review with Google's Paper Assistant Tool

Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem proving. However, this rapid acceleration is creating a systemic challenge: traditional human peer review cannot scale to match the influx of AI-assisted science. Ultimately, to resolve this tension, we must also deploy AI to accelerate the verification and review process itself. Authors: Rajesh Jayaram, Drew Tyler, David Woodruff.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem proving.

Primary paperarxivcs.LG
Original
Artificial Intelligence / Machine Learning
NVIDIA Technical Blog6/26/2026
Recently

Deploy a Production-Ready NVIDIA AI-Q Blueprint on Oracle Cloud Infrastructure

AI agents have changed a lot in the last two years. The first could only answer one question at a time. Then came multi-turn chat, where the model could keep...

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: AI agents have changed a lot in the last two years.

Official source
Original
Artificial Intelligence / Machine Learning
NVIDIA Technical Blog6/26/2026
Recently

Creating the NVIDIA Nemotron 3 Ultra NVFP4 Checkpoint with NVIDIA Model Optimizer

As context windows grow longer, moving large model weights efficiently becomes critical to performance. A common way to address this is quantization, an... As context windows grow longer, moving large model weights efficiently becomes critical to performance.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: As context windows grow longer, moving large model weights efficiently becomes critical to performance.

Official source
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv6/26/2026
Recently

Agent-Native Immune System: Architecture, Taxonomy, and Engineering

The transition from static chat bots to autonomous agents--equipped with persistent memory, tool-use protocols, and multi-agent collaboration--has fundamentally expanded the AI threat landscape. Current defense mechanisms, such as perimeter security and training-time alignment, remain external to the agent's active reasoning loop. Consequently, they fall short: a fully aligned agent remains highly vulnerable to runtime hijacking via memory poisoning, tool-chain manipulation, or multi-agent protocol attacks. Authors: Bo Shen, Lifeng Chang, Tianyuan Wei.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: The transition from static chat bots to autonomous agents--equipped with persistent memory, tool-use protocols, and multi-agent collaboration--has fundamentally expanded the AI threat landscape.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv6/26/2026
Recently

Agentic Hardware Design as Repository-Level Code Evolution

We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled into a project pack containing domain knowledge, an executable evaluator, an acceptance predicate, and a git/runtime policy; a hands-free agent loop then evolves an isolated git worktree, using repository operations for state management, tracing, and replay. This extends prior works of repository-scale self-evolution from EDA software systems, to hardware-design artifacts themselves. Authors: Cunxi Yu, Chenhui Deng, Nathaniel Pinckney.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution.

Primary paperarxivcs.AR
Original
Automation / Agentic Systems
arXiv6/26/2026
Recently

Govern the Repository, Not the Agent: Measuring Ecosystem-Level Risk in AI-Native Software

Autonomous coding agents now open and merge pull requests in shared repositories at scale, and the field evaluates them the way it has always evaluated components, one agent at a time, on isolated benchmark tasks. Yet agents that each pass their own tests still leave repositories that accumulate problems no single contribution accounts for. We ask whether this problem belongs to the individual agent or to the repository where it accumulates. Authors: Daniel Russo.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Autonomous coding agents now open and merge pull requests in shared repositories at scale, and the field evaluates them the way it has always evaluated components, one agent at a time, on isolated benchmark tasks.

Primary paperarxivcs.SE
Original
Automation / Agentic Systems
arXiv6/26/2026
Recently

Towards Value-Constrained Credit Assignment in Fully Delegated AI Cooperatives

We propose a framework for reward allocation in fully delegated AI cooperatives where humans are represented by agents that contribute data and participate in model updates under heterogeneous value constraints. The key idea is to credit only those updates that remain admissible after screening them against each principal's value profile. We formulate value-conditioned gradient filtering, online marginal contribution signals, and cumulative revenue settlement within a traversal learning (TL) substrate. Authors: Young Yoon, Jimin Kim, Soyeon Park.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: We propose a framework for reward allocation in fully delegated AI cooperatives where humans are represented by agents that contribute data and participate in model updates under heterogeneous value constraints.

Primary paperarxivcs.LG
Original
Automation / Agentic Systems
arXiv6/26/2026
Recently

LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior

Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years. However, existing large language model (LLM)-based agents often exhibit behaviors that are misaligned with their partners or inconsistent with the environment state, leading to inefficient cooperation and poor task success. To address this challenge, we propose a novel framework, Learning Laws of Cooperation (LLawCo), that enables embodied agents to autonomously align with both their partners and task objectives. Authors: Qinhong Zhou, Chuang Gan, Anoop Cherian.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years.

Primary paperarxivcs.LG
Original

Archived section

Research Papers · 2

Research Papers
arXiv6/26/2026
Recently

Typing Behavior in Human-LLM Interaction: Keystroke Dynamics Reveal Cognitive Effort During Prompting

As Large Language Models (LLMs) become increasingly integrated into daily routines, understanding how users interact with these systems is crucial for effective human-AI collaboration. This work investigates keystroke dynamics as a behavioral measure of user mental effort and perceived output usefulness in human-LLM interaction. We conducted a user study (N = 36) to examine how task difficulty (easy vs. Authors: Laura Schütz, Yousri Cherif, Clara Sayffaerth.

Why it matters

Read this for the paper's specific claim in Research Papers: As Large Language Models (LLMs) become increasingly integrated into daily routines, understanding how users interact with these systems is crucial for effective human-AI collaboration.

Primary paperarxivcs.HC
Original
Research Papers
arXiv6/26/2026
Recently

Functional outcomes and naturalistic engagement with a purpose-built conversational AI for mental health (Ash)

Background: Conversational AI chatbots designed for mental health may offer an accessible, scalable avenue for supporting psychological well-being, yet prior evaluations have largely focused on clinical symptom reduction rather than broader indicators of day-to-day functioning, and have rarely monitored for potential harms such as inflated self-perception. Objective: We examined within-person change in psychological functioning indicators among real-world users of Ash, a purpose-built conversational AI for mental health support, over the first four weeks of use, and whether these changes were associated with engagement metrics. Methods: In this single-arm observational cohort study, new users (n = 1,284) completed in-app single-item measures of psychological functioning (life satisfaction, relationship satisfaction, sleep quality, behavioral activation), working alliance, and grandiosity (inflated self-perception), at baseline and Week 4. Authors: Kristen M. Van Swearingen, Thomas D. Hull, Karthik V. Sarma.

Why it matters

Read this for the paper's specific claim in Research Papers: Background: Conversational AI chatbots designed for mental health may offer an accessible, scalable avenue for supporting psychological well-being, yet prior evaluations have largely focused on clinical symptom reduction rather than broader indicators of day-to-day functioning, and have rarely monitored for potential harms such as inflated self-perception.

Primary paperarxivcs.HC
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv6/26/2026
Recently

PA-BiCoop: A Primary-Auxiliary Cooperative Framework for General Bimanual Manipulation

Bimanual manipulation is essential for advanced robotic systems because it offers higher efficiency and flexibility compared to single-arm configurations. However, existing approaches either lack inter-arm interaction or ignore the need for a dynamic division of labor, treating the arms as functionally equivalent. To address these limitations, this paper draws inspiration from human bimanual manipulation where one arm handles core operations and the other provides auxiliary support, and proposes PA-BiCoop, a new single-model bimanual cooperation framework with dynamic primary-auxiliary arm differentiation. Authors: Bai Qicheng, Wang Ziru, Ma Teli.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Bimanual manipulation is essential for advanced robotic systems because it offers higher efficiency and flexibility compared to single-arm configurations.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv6/26/2026
Recently

SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation

Training and evaluating robot policies in the real world is costly and difficult to scale. We introduce SimFoundry, a modular and automated system for zero-shot real-to-sim scene construction from a video. SimFoundry generates sim-ready digital twins and supports object, scene, and task editing, enabling the automated generation of diverse digital cousins: affordance-preserving variations of reconstructed real-world scenes. Authors: Nadun Ranawaka, Josiah Wong, Wei-Lin Pai.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Training and evaluating robot policies in the real world is costly and difficult to scale.

Primary paperarxivcs.RO
Original
Embedded Systems
Hackaday6/28/2026
Recently

Reachy Mini Desktop Robot Gets All-local, Conversational AI

Reachy Mini is a limbless desktop robot from Hugging Face made for human interaction experiments, and to give you an idea of what it's like is a guide on how …read more

Why it matters

Read this for the engineering context in Embedded Systems: Reachy Mini is a limbless desktop robot from Hugging Face made for human interaction experiments, and to give you an idea of what it's like is a guide on how …read more

Trusted sourceArtificial IntelligenceRobots Hacks
Original
Embedded Systems
arXiv6/26/2026
Recently

WARP-RM: A Warp-Augmented Relative Progress Reward Model for Data Curation

Scaling imitation learning requires large datasets, yet human teleoperation inevitably produces mixed-quality demonstrations containing hesitations and recoveries. Prior frame-level progress reward models supervise on absolute temporal progress proxies that suffer from label noise, or require costly human annotations to define subtask boundaries. We present WARP (Warp-Augmented Relative Progress), a novel fully self-supervised algorithm for learning dense, signed relative progress magnitudes directly from successful demonstrations. Authors: Justin Yu, Andrew Goldberg, Kavish Kondap.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Scaling imitation learning requires large datasets, yet human teleoperation inevitably produces mixed-quality demonstrations containing hesitations and recoveries.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv6/26/2026
Recently

CacheMPC: Certified Cached Model Predictive Control for Quadruped Locomotion

Model Predictive Control (MPC) is the standard predictive layer in hierarchical quadruped controllers, but the per-cycle QP solve limits the update rate achievable on embedded processors. Because legged gaits revisit a bounded region of state space, MPC solutions admit caching and reuse. This paper proposes Certified CacheMPC: a Locality-Sensitive-Hashed cache of horizon contact-force trajectories, partitioned by contact mode, retrieved at query time and accepted only when an a-posteriori per-query certificate confirms primal feasibility and a Lagrangian dual-gap upper bound on cost suboptimality. Authors: Nimesh Khandelwal, Mehul Anand, Shakti S. Gupta.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Model Predictive Control (MPC) is the standard predictive layer in hierarchical quadruped controllers, but the per-cycle QP solve limits the update rate achievable on embedded processors.

Primary paperarxivcs.RO
Original

Archived section

Computer Systems · 4

Computer Systems
CNCF Blog6/26/2026
Recently

Security Profiles Operator v1: Stable APIs, Security Hardened, and Shaping Upstream Kubernetes

Linux provides powerful kernel-level security mechanisms, seccomp, SELinux, and AppArmor, that restrict what containerized workloads can do. Each uses profiles that define permitted behavior, but writing, distributing, and maintaining those profiles by hand is tedious and...

Why it matters

Read this for the official technical update in Computer Systems: Linux provides powerful kernel-level security mechanisms, seccomp, SELinux, and AppArmor, that restrict what containerized workloads can do.

Official sourceBlog
Original
Computer Systems
LWN.net6/26/2026
Recently

Initiating writeback earlier

Writeback is the process of ensuring that dirty pages or folios in the page cache are flushed to the disk, so that changes to those files are made persistent. In a filesystem-track session at the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit, Jeff Layton wanted to discuss whether the writeback operation should be initiated earlier than it is today. The consensus seemed to be that it should be done earlier, but the path toward making that happen was less clear.

Why it matters

Read this for the concrete reporting in Computer Systems: Writeback is the process of ensuring that dirty pages or folios in the page cache are flushed to the disk, so that changes to those files are made persistent.

Trusted source
Original
Computer Systems
LWN.net6/26/2026
Recently

Reports from OSPM 2026, day three

The Power Management and Scheduling in the Linux Kernel Summit, which still goes by the historical acronym OSPM, was held in Cambridge, UK, in mid-April. As has become traditional, the presenters at that event have since written summaries of their sessions, and this work has kindly been made available to LWN for publication. The third day's sessions covered a wide range of topics, including GPU affinity, profile-guided scheduling, paravirtualization scheduling, quality of service, and more.

Why it matters

Read this for the concrete reporting in Computer Systems: The Power Management and Scheduling in the Linux Kernel Summit, which still goes by the historical acronym OSPM, was held in Cambridge, UK, in mid-April.

Trusted source
Original
Computer Systems
LWN.net6/28/2026
Recently

Kernel prepatch 7.2-rc1

2-rc1 kernel prepatch is out for testing. Linus said: "So two weeks have passed, and the merge window is closed.

Why it matters

Read this for the concrete reporting in Computer Systems: Linus said: "So two weeks have passed, and the merge window is closed.

Trusted source
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
CNCF Blog6/29/2026
Recently

etcd-operator joins Cozystack with a new v1alpha2 API

The etcd-operator project, which develops an operator for deploying and maintaining etcd clusters on Kubernetes, has been donated to the Cozystack project. Alongside the donation, a from-scratch implementation of the operator has been published under a...

Why it matters

Read this for the official technical update in Developer Tools / Open Source: The etcd-operator project, which develops an operator for deploying and maintaining etcd clusters on Kubernetes, has been donated to the Cozystack project.

Official sourceBlog
Original
Developer Tools / Open Source
Kubernetes Blog6/26/2026
Recently

Open source maintainership in the age of AI

AI has really changed the game around software development. More people are leveraging AI than ever to contribute patches to projects they use. To me, this is a good thing as more folks will contribute patches rather than fork or not fix them.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: AI has really changed the game around software development.

Official source
Original
Developer Tools / Open Source
arXiv6/26/2026
Recently

Humanizing Automatically Generated Unit Test Suites with LLM-Based Refactoring

Search-based test generation tools such as EvoSuite produce compilable and high-coverage unit tests at scale, but their suites are often hard to read and maintain. LLMs can generate more natural tests, yet direct generation remains brittle, with compilation rates of only 51-78% in our study. We introduce TestHumanizer, a hybrid SBST+LLM approach that uses LLMs as controlled refactoring layers over compilable SBST suites to improve naming, structure, and developer-oriented clarity while preserving behavior and compilation validity. Authors: Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Search-based test generation tools such as EvoSuite produce compilable and high-coverage unit tests at scale, but their suites are often hard to read and maintain.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
arXiv6/26/2026
Recently

CrossLangFuzzer: Differential Testing of Cross-Language JVM Compilers

Modern JVM software increasingly integrates multiple programming languages, such as Java, Kotlin, Groovy, and Scala, within a single application. Supporting such interoperability requires JVM compilers to perform cross-language compilation while reconciling subtle semantic differences across language boundaries. Errors in this process can lead to critical miscompilations, yet existing compiler testing techniques focus exclusively on isolated, singlelanguage compilation. Authors: Xiaotian Ma, Qiong Feng, Yongqiang Tian.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Modern JVM software increasingly integrates multiple programming languages, such as Java, Kotlin, Groovy, and Scala, within a single application.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
GitHub Blog6/26/2026
Recently

GitHub and UNDP team up to advance development priorities in Ghana with open source

GitHub joined the United Nations Development Programme in Ghana to explore how open source governance can support one of West Africa's most ambitious digital reform efforts. The post GitHub and UNDP team up to advance development priorities in Ghana with open source appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: GitHub joined the United Nations Development Programme in Ghana to explore how open source governance can support one of West Africa's most ambitious digital reform efforts.

Official sourceOpen SourceSocial impact
Original

Archived section

Cloud / Infrastructure · 1

Cloud / Infrastructure
Microsoft Azure Blog6/26/2026
Recently

The performance dividend: Optimizing PostgreSQL on Azure directly in Visual Studio Code

Poor database performance is never just a database problem. In enterprise teams, it shows up as missed SLAs, delayed releases, frustrated development teams, and rising operational risk. The performance problem compounds further in business impact, often resulting in frustrated customers, retention and conversion risk, and lost revenue.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Poor database performance is never just a database problem.

Official sourceDatabasesHybrid + multicloud
Original