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Artificial Intelligence / Machine Learning · 5

Automation / Agentic Systems · 5

Research Papers · 5

Embedded Systems · 5

Computer Systems · 4

Developer Tools / Open Source · 4

Cloud / Infrastructure · 2

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/23/2026
Recently

MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education

Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or single-turn feedback, rather than organizing an entire clinical case into a decision-centered learning trajectory. We introduce MedGame, a framework that transforms static clinical cases into structured, executable storytelling games. MedGame uses a dual-engine design: a Medical Narrative Designer synthesizes case-grounded clinical storylines with states and decision nodes, while a Story Director converts them into dependency-aware multimodal orchestration plans rendered by our released interactive platform. Authors: Qian Wu, Xinrong Zhou, Zizhan Ma.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or single-turn feedback, rather than organizing an entire clinical case into a decision-centered learning trajectory.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv7/23/2026
Recently

3D-Aware VLMs with Implicit and Explicit Geometries

Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that require fine-grained spatial understanding and reasoning. To bridge this gap, we present VLM-IE3D, a unified framework that enhances the 3D spatial awareness of VLMs by equipping them with both implicit and explicit 3D geometries learned from RGB videos. Our VLM-IE3D introduces Implicit Geometry Tokens (IGTs) that capture high-level geometric priors from input videos, as well as complementary Explicit Geometry Tokens (EGTs) that encode detailed geometric structures from reconstructed 3D attributes. Authors: Wenhao Li, Xueying Jiang, Quanhao Qian.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that require fine-grained spatial understanding and reasoning.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
arXiv7/23/2026
Recently

Surprisal Theory is Tautological (without Rational Grounding)

Surprisal theory holds that the human processing difficulty of a linguistic unit in context is an affine function of its surprisal under some language model. I argue this claim is a tautology without further constraint: for any non-negative difficulty measure over units in context, there exists a language model whose surprisal is an affine function of it under mild technical conditions. Therefore, because any pattern of difficulty is consistent with some language model, without an additional constraint on the language model, surprisal theory makes no falsifiable predictions. Authors: Ryan Cotterell.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Surprisal theory holds that the human processing difficulty of a linguistic unit in context is an affine function of its surprisal under some language model.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv7/23/2026
Recently

Synthetic data generation framework for quality control automation in gravure printing

Quality control in printing, particularly in rotogravure printing, still depends on slow, costly, and subjective manual inspection. Automated surface defect detection is critical for maintaining high-quality standards in rotogravure printing. Deep learning models give prospects for automation. Authors: Korota Arsène Coulibaly, Mohamed Hamlich, Khalid Hmali.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Quality control in printing, particularly in rotogravure printing, still depends on slow, costly, and subjective manual inspection.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
Apple Machine Learning Research7/23/2026
Recently

LEAD: Breaking the No-Recovery Bottleneck in Long-Horizon Reasoning

Long-horizon execution in Large Language Models (LLMs) remains unstable even when high-level strategies are provided. Evaluating on controlled algorithmic puzzles, we demonstrate that while decomposition is essential for stability, extreme decomposition creates a "no-recovery bottleneck". We show that this bottleneck becomes critical due to highly non-uniform error distribution, where consistent errors on a few "hard" steps become irreversible.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Long-horizon execution in Large Language Models (LLMs) remains unstable even when high-level strategies are provided.

Official source
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/23/2026
Recently

Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems

Production AI agents' failures are less often due to an inability to reason well and more often because they cannot manage what is in their reasoning context: conversation histories, large prompts, large tool definitions, and ballooning tool outputs. Agents drown in their own accumulating history while paying a token cost that grows every turn, producing missing recalls within and across conversations. The incumbent response treats this as a storage-and-retrieval problem. Authors: Gaurav Dadhich.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Production AI agents' failures are less often due to an inability to reason well and more often because they cannot manage what is in their reasoning context: conversation histories, large prompts, large tool definitions, and ballooning tool outputs.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/23/2026
Recently

Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry

AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments. This democratization enables rapid local innovation, but it also creates a reliability gap: agents that appear to users as simple productivity artifacts may depend on changing models, tools, retrieval sources, permissions, prompts, schedules, and external services. These dependencies can cause silent degradation long after deployment, even when no user directly modifies the agent. Authors: Natan Levy, Harel Berger.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/23/2026
Recently

Agentic coding without the cloud: evaluating open-weight large language models on longitudinal data preparation tasks

Large language models (LLMs) and agents are now widely used tools in code development, with data typically sent to third-party cloud-based models. Their adoption in research using personal data is constrained by governance requirements that typically prohibit data transmission to external services. Locally deployable open-weight models offer an alternative since sensitive data never leave the local environment. Authors: Mack Nixon, Liam Wright, Yevgeniya Kovalchuk.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Large language models (LLMs) and agents are now widely used tools in code development, with data typically sent to third-party cloud-based models.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/23/2026
Recently

OpenForgeRL: Train Harness-native Agents in Any Environment

Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to external systems. While powerful, these complex harnesses also make agents hard to train end-to-end with open infrastructure, whose SFT/RL stacks cannot natively express stateful, multi-process harness inference. To address this, we present OpenForgeRL, an open-source framework for training harness-based agents end-to-end in diverse environments. Authors: Xiao Yu, Baolin Peng, Ruize Xu.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to external systems.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/23/2026
Recently

Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections

Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, which typically struggle with combinatorial action spaces, reliance on privileged information, or rigid agent designs. We propose Master-Agent Proto-plan System (MAPS), a hierarchical deep reinforcement learning (DRL) architecture in which a centralized Master agent generates a compact, continuous embedding, denoted as proto-plan, that encodes a global coordination strategy. Decentralized Worker agents integrate this embedding with local observations to execute vehicle-specific control, decoupling strategic intent from tactical execution and enabling independent optimization of each module. Authors: Gil Lifshits, Igal Bilik, Gilad Katz.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, which typically struggle with combinatorial action spaces, reliance on privileged information, or rigid agent designs.

Primary paperarxivcs.LG
Original

Archived section

Research Papers · 5

Research Papers
arXiv7/23/2026
Recently

Where You Tap Matters: A Probe-and-Model Benchmark for Open-Set RF Fingerprinting

Radio Frequency Fingerprint Identification (RFFI) enables transmitter identification at the physical layer by learning device-specific impairments from received signals, yet the literature is inconsistent about where in the receiver chain those samples should be collected., carrier recovery, gain normalization, pulse shaping, and timing recovery, they can either tighten within-transmitter variability or suppress the features RFFI requires for classification. We present a systematic real-world evaluation of open-set, reconstruction-error RFFI using data collected at five probe points along a standard BPSK receiver chain. Authors: Gabriele Oligeri, Savio Sciancalepore, Ingrid Huso.

Why it matters

Read this for the paper's specific claim in Research Papers: , carrier recovery, gain normalization, pulse shaping, and timing recovery, they can either tighten within-transmitter variability or suppress the features RFFI requires for classification.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/23/2026
Recently

Sources of Inequity and Fairness Risks inWellbeing Sensing

, depression, cognitive load)., hospitals, universities), yet fairness research remains limited---primarily to post-hoc, identity-based comparisons of model performance. However, passive sensing combines heterogeneous sensing infrastructures, indirect behavioral inference, and longitudinal deployment---characteristics that, while not exclusive to the domain, are jointly pronounced here and raise two underexplored questions: (1) what additional sources of inequity arise from these characteristics, and (2) how do such inequities propagate beyond algorithmic audits across the system lifecycle? Authors: Han Zhang, Vedant Das Swain, Koustuv Saha.

Why it matters

Read this for the paper's specific claim in Research Papers: , hospitals, universities), yet fairness research remains limited---primarily to post-hoc, identity-based comparisons of model performance.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/23/2026
Recently

Transparent by Design, Usable in Practice? A Formative Usability Study of a Conversational Product Advisor

Large language models can make conversational product advisors fluent but opaque. If they hide the logic behind a ranking and the evidence for a recommendation inside natural-language replies, they challenge users' ability to understand, trust, and steer the results. One response is to build transparency into the advisor. Authors: Kevin Schott, Dagmar Kern, Daniel Hienert.

Why it matters

Read this for the paper's specific claim in Research Papers: Large language models can make conversational product advisors fluent but opaque.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/23/2026
Recently

Unconditional Unclonable Encryption

We give an unconditional construction of information-theoretically secure one-time private-key unclonable encryption scheme for one-bit messages, with efficient encryption and decryption and exponentially small unclonable-indistinguishability advantage. Authors: Prabhanjan Ananth, Amit Sahai.

Why it matters

Read this for the paper's specific claim in Research Papers: We give an unconditional construction of information-theoretically secure one-time private-key unclonable encryption scheme for one-bit messages, with efficient encryption and decryption and exponentially small unclonable-indistinguishability advantage.

Primary paperarxivquant-ph
Original
Research Papers
arXiv7/23/2026
Recently

A Needs Assessment for Measuring Geographic - Legislative Associations in the U.S. House of Representatives

Political legislation affects the well-being and livelihoods of constituents. S. Congress a representative's voting record on bills and legislation is public. Authors: Ashu Gupta, Cameron Owens, Benjamin Wilson-Langman.

Why it matters

Read this for the paper's specific claim in Research Papers: Political legislation affects the well-being and livelihoods of constituents.

Primary paperarxivcs.HC
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/23/2026
Recently

Interoperability of Electric Drive Models using HELICS

Accurate modeling and simulation are essential for the effective design, testing, and evaluation of electric machine systems., C, MATLAB, Python) and the separation of components such as inverters and controllers across diverse environments. These challenges are amplified by the growing use of advanced simulation platforms like Hardware-in-the-Loop (HIL) and Controller-HIL, which require repeated adaptations for compatibility. Authors: Ajay Pratap Yadav.

Why it matters

Read this for the paper's specific claim in Embedded Systems: , C, MATLAB, Python) and the separation of components such as inverters and controllers across diverse environments.

Primary paperarxiveess.SY
Original
Embedded Systems
arXiv7/23/2026
Recently

AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites. We present AXIS, a growable community-driven data engine and benchmark for scalable robot learning, which enables browser-based teleoperation for large-scale demonstration collection, automatically generates and validates new manipulation tasks, and transforms community-collected demonstrations into training-ready data through automated success checking, quality filtering, trajectory smoothing, and visual and physics-based augmentation. The AXIS dataset currently contains 207 diverse tasks and 50K+ trajectories. Authors: Mengfei Zhao, Dihong Huang, Yikai Tang.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites.

Primary paperarxivcs.RO
Original
Embedded Systems
Hackaday7/24/2026
Recently

Codeberg Bans Cryptocurrency and LLM-Generated Code Projects

Community-led open source project hosting site Codeberg has formally announced that projects whose code is largely or fully machine-generated through LLMs and other 'AI' tools will no longer be welcome.

Why it matters

Read this for the engineering context in Embedded Systems: Community-led open source project hosting site Codeberg has formally announced that projects whose code is largely or fully machine-generated through LLMs and other 'AI' tools will no longer be welcome.

Trusted sourceArtificial IntelligenceNews
Original
Embedded Systems
arXiv7/23/2026
Recently

Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation

Compositional generalization is essential for robot to follow diverse instructions. However, pretrained policies are known to take shortcuts, deferring to salient cues rather than grounding language., reusable semantic components such as color, verb, object, size, and spatial attribute. Authors: Yu Qi, Zhang Ye, Xinyi Xu.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Compositional generalization is essential for robot to follow diverse instructions.

Primary paperarxivcs.RO
Original
Embedded Systems
Hackster.io7/24/2026
Recently

MNT Pulls the Keyboard, Trackball From Its Pocket Reform to Grace Even the Tiniest of Desks

Open hardware specialist MNT Research, the firm behind the Reform family of laptops and an upcoming ultra-compact desktop, has launched its latest device: a standalone version of the ortholinear keyboard and trackball originally designed for the Pocket Reform. "Equipped with a micro-optical trackball, the MNT Pocket Reform Standalone Keyboard makes for a comfy couch or desk setup that doesn't require a mouse," the company writes of its latest launch. " The mechanical keyboard, with an integrated four-button trackball underneath, was originally developed for the Pocket Reform — a netbook-inspired ultra-portable laptop that, in turn, spun out from the earlier Reform family of full-size laptops.

Why it matters

Read this for the engineering context in Embedded Systems: Open hardware specialist MNT Research, the firm behind the Reform family of laptops and an upcoming ultra-compact desktop, has launched its latest device: a standalone version of the ortholinear keyboard and trackball originally designed for the Pocket Reform.

Trusted source
Original

Archived section

Computer Systems · 4

Computer Systems
LWN.net7/23/2026
Recently

An operations structure for swap devices

One of the ideas raised at the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit (LSFMM+BPF) was the creation of an operations structure for the swap subsystem. Like many parts of the kernel, the swap layer evolved over time, with pieces being added as needed; the end result of this evolution is rarely what one would expect had the subsystem been designed today. The interface between the swap layer and the devices it uses is just one example.

Why it matters

Read this for the concrete reporting in Computer Systems: One of the ideas raised at the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit (LSFMM+BPF) was the creation of an operations structure for the swap subsystem.

Trusted source
Original
Computer Systems
arXiv7/23/2026
Recently

Windowed-MTP: Removing the Full-Context Draft-KV Tax at Million-Token Context

Speculative decoding accelerates autoregressive generation by having a cheap draft propose tokens that a target verifies in parallel. Frontier models increasingly ship a built-in Multi-Token-Prediction (MTP/NEXTN) draft head under the assumption that the draft is negligibly cheap. At million-token context this breaks: an MTP draft head typically runs full attention over the entire KV cache at every draft step, so its read grows linearly with context and comes to dominate the draft cost -- precisely where speculation is most valuable. Authors: Alagappan Valliappan.

Why it matters

Read this for the paper's specific claim in Computer Systems: Speculative decoding accelerates autoregressive generation by having a cheap draft propose tokens that a target verifies in parallel.

Primary paperarxivcs.LG
Original
Computer Systems
LWN.net7/23/2026
Recently

Mourning Dan Williams

I have just received the shocking news that Dan Williams, a longtime, high-profile kernel developer, has passed away. I knew him primarily through his long service on the Linux Foundation Technical Advisory Board; he was always a strong, thoughtful, and intelligent presence. Dan will be deeply missed.

Why it matters

Read this for the concrete reporting in Computer Systems: I have just received the shocking news that Dan Williams, a longtime, high-profile kernel developer, has passed away.

Trusted source
Original
Computer Systems
LWN.net7/24/2026
Recently

An update on netkit and the use of BPF in user space

Daniel Borkmann led a session at the 2026 Linux Filesystem, Memory-Management, and BPF Summit about the progress that has been made with netkit, the subsystem that allows virtual machines (VMs) running on Linux to perform networking efficiently. When that did not fill the full time, he went on to discuss his idea for using BPF to live-patch user-space applications. While netkit is making progress, and can now support zero-copy receipt of packets into a VM in a network namespace, the idea of using BPF for patching user-space programs remains entirely speculative.

Why it matters

Read this for the concrete reporting in Computer Systems: Daniel Borkmann led a session at the 2026 Linux Filesystem, Memory-Management, and BPF Summit about the progress that has been made with netkit, the subsystem that allows virtual machines (VMs) running on Linux to perform networking efficiently.

Trusted source
Original

Archived section

Developer Tools / Open Source · 4

Developer Tools / Open Source
arXiv7/23/2026
Recently

From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs

Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings. Large language models can synthesize executable Rust tests, but their outputs often violate API preconditions, remain shallow, or reduce concurrency to accidental sequential traces. Conversely, model-based and systematic testing techniques provide semantic control but commonly require substantial handwritten code to turn abstract scenarios into executable tests. Authors: Kaiwen Zhang, Guanjun Liu.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
NVIDIA Technical Blog7/23/2026
Recently

Debugging Ray Tracing Applications Using NVIDIA OptiX Toolkit

NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU. Applications using OptiX can fail in ways... NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU.

Official source
Original
Developer Tools / Open Source
GitHub Blog7/23/2026
Recently

The case for a cooldown: Why Dependabot now waits before issuing version updates

A new default three-day cooldown delays version update pull requests so maintainers and security researchers can address findings in a release before it gets into your code. The post The case for a cooldown: Why Dependabot now waits before issuing version updates appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: A new default three-day cooldown delays version update pull requests so maintainers and security researchers can address findings in a release before it gets into your code.

Official sourceSupply chain securityDependabot
Original
Developer Tools / Open Source
CNCF Blog7/24/2026
Recently

OpenTelemetry has graduated… Now what?

In case you missed it: OpenTelemetry (OTel) has officially achieved CNCF graduated status! It now stands proudly alongside amazing open source projects such as Kubernetes and Prometheus, to name just a few. It's been a long journey, and we're very...

Why it matters

Read this for the official technical update in Developer Tools / Open Source: In case you missed it: OpenTelemetry (OTel) has officially achieved CNCF graduated status!

Official sourceBlog
Original

Archived section

Cloud / Infrastructure · 2

Cloud / Infrastructure
LWN.net7/24/2026
Recently

De Vlieger: The Fedora 45 sausage factory

Fedora contributor Simon de Vlieger has published a blog post with a walkthrough of how the project turns source code and packages into the final release that users install on their systems. It follows the a package from a packager's git push to a composed release: ISOs, cloud images, container images, and OSTree deployments. The walkthrough describes how the Fedora 'sausage' is created as of Fedora 45, things change all the time; I hope to have time to update this document every cycle or every few cycles of Fedora releases so there's both history and people can find up to date information.

Why it matters

Read this for the concrete reporting in Cloud / Infrastructure: Fedora contributor Simon de Vlieger has published a blog post with a walkthrough of how the project turns source code and packages into the final release that users install on their systems.

Trusted source
Original
Cloud / Infrastructure
Cloudflare Blog7/24/2026
Recently

BGP ORIGIN attribute manipulation and its impact on the Internet

By doing in-depth testing, we found nearly 70% of BGP paths experience ORIGIN attribute rewrites by transit providers seeking traffic advantages. We examine the global impact of this practice and argue for deprecating ORIGIN in route selection.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: By doing in-depth testing, we found nearly 70% of BGP paths experience ORIGIN attribute rewrites by transit providers seeking traffic advantages.

Official sourceBetter InternetBGP
Original