Scout Daily
10
Case Studies
25
News Items
Updated 17 Aug 2026, 07:10 UTC
IT Relevance: High / Novelty: High / Value: High⏳ Evaluating
43

Knowing When to Stop: Bayesian Optimal Stopping for LLM Evaluations

Toby D. Pilditch · Academic Institution · 14 Aug 2026

This research solves the problem of inefficient evaluation methods for Large Language Models (LLMs) by introducing a framework that adaptively stops testing when estimates are precise enough. The researchers built a precision-based adaptive stopping framework called optstop, which treats evaluation as a sequential measurement problem. The result is a more efficient evaluation process, but it's not directly relevant to cloud infrastructure management.

HOW TO APPLY THIS

Not directly applicable to IT infrastructure work

View Technical Reasoning
IMPACT15/25
MATURITY8/25
MONETISATION20/25

High novelty as it proposes a new approach to LLM evaluations. High IT relevance due to its direct impact on LLM API performance and MLOps. High value within 90 days as IT consultants can use this to optimize LLM evaluations and improve client satisfaction.

AI-deployment, IT-relevance:High⏳ Evaluating
43

AgentRewind: Recoverable Execution for Long-Horizon LLM Agents

Yu Zhuang, Kefei Chen, Yitong Duan, Shuxin Zheng · Academic Institution · 14 Aug 2026

This research solves the problem of errors in long-horizon execution of Large Language Model (LLM) agents by building a recovery framework called AgentRewind, which records checkpoints to enable recovery after errors occur, resulting in more reliable agent execution. The framework allows agents to rewind and recover from errors, reducing the impact of early errors on overall execution. This research is relevant to IT work in cloud infrastructure, particularly in managing LLM-based systems.

HOW TO APPLY THIS

If you manage LLM-based systems, here is what to do: review your current error handling mechanisms, consider integrating a recovery framework like AgentRewind, and evaluate the potential benefits of checkpoint-based recovery for your specific use case. This flags a risk: if your org uses LLM agents for critical tasks, check your error handling and recovery processes immediately to minimize potential downtime. Not directly applicable to general IT infrastructure work outside of LLM-based systems.

View Technical Reasoning
IMPACT18/25
MATURITY25/25
MONETISATION0/25

Novelty is high due to the introduction of AgentRewind, a runtime recovery framework for LLM agents. IT relevance is high as it deals with agentic systems and addresses a key challenge in their deployment. Value in 90 days is moderate, as IT engineers may find it useful for improving reliability of LLM agents but it would still require further development and testing.

Software Security, LLM APIs⏳ Evaluating
35

Finding Vulnerabilities via LLM-Augmented Semantics-Aware Type-Checking

Ruizhe Wang, Meng Xu, N. Asokan · Academic Institution · 14 Aug 2026

This research solves the problem of detecting software vulnerabilities by proposing a new approach that uses semantics-aware type-checking, the authors built SETYPE, a type system that can identify vulnerabilities by understanding the meanings of code elements, the result is a more effective way to detect vulnerabilities. This approach can help improve the security of software systems. It focuses on enhancing static analysis techniques.

HOW TO APPLY THIS

If you manage cloud-based software applications, here is what to do: review your current static analysis tools, consider integrating SETYPE or similar semantics-aware type systems, and assess how this new approach can enhance your vulnerability detection capabilities.

View Technical Reasoning
IMPACT15/25
MATURITY20/25
MONETISATION0/25

This paper proposes a novel approach to vulnerability detection in software systems. The LLM-augmented semantics-aware type-checking approach is relevant to IT engineers who work with software security and may be affected by LLM APIs. However, the paper is primarily focused on the theoretical aspect of the approach and does not provide immediate actionable steps for IT engineers or consultants to deploy within 90 days. Therefore, the VALUE_90_DAYS score is relatively low. The NOVELTY score is high because the approach is novel and reveals something surprising about tools and systems used in software security. The IT_RELEVANCE score is moderate because while the paper is relevant to software security, it does not directly involve current IT infrastructure or software engineering best practices.

IT infrastructure⏳ Evaluating
25

Evolve Vision-Language-Action Model into an Agent with On-the-fly Tool-use

Yi Ding, Yanzhao Yu, Xili Dai, Xianbiao Qi · Academic Institution · 14 Aug 2026

This research solves the problem of complex action solution spaces in Visual-Language-Action models by creating an Agentic Robot with Tool-use framework that integrates tool-use into these models, resulting in improved generalizability and reduced data dependency. The authors built a tool-injection framework that tunes VLA models to leverage off-the-shelf tool modules. This research is not directly relevant to IT infrastructure work.

HOW TO APPLY THIS

Not directly applicable to IT infrastructure work, as it focuses on robotics and artificial intelligence, so no action is required for cloud infrastructure management.

View Technical Reasoning
IMPACT15/25
MATURITY10/25
MONETISATION0/25

Novelty: High maturity agentic system; Relevance: Tool injection for robotics, relevant to software agnostic systems; Value in 90 days: Limited applicability to IT infrastructure without significant adaptation

LLM, Legacy Code⏳ Evaluating
20

Validating LLM-Modernized Scientific Software Through Differential Fault Injection

Evan Coleman, Yuzhong Shen, Masha Sosonkina, Peng Xu · Academic Institution · 14 Aug 2026

This research solves the problem of validating large language model modernizations of scientific software by testing their response to faults and perturbations. The researchers built a differential fault-injection validation method to compare the original and modernized code. The result is a method to ensure that modernized software retains the original code's reliability.

HOW TO APPLY THIS

Not directly applicable to IT infrastructure work, as it focuses on validating scientific software modernization through fault injection, which is a specialized task for software development and testing.

View Technical Reasoning
IMPACT0/25
MATURITY15/25
MONETISATION5/25

Novel in approach to validating LLM modernized scientific software. Relevance in IT is moderate due to mention of LLMs and legacy code. However, direct impact to IT engineers' work is somewhat limited as the focus is on scientific software validation. Value within 90 days is low due to the specialized nature of the problem.

cybersecurity, threat intelligence⏳ Evaluating
15

STINER: Automated Extraction of Strategic Cyber Threat Intelligence from X

Yasir Ech-Chammakhy, Oussama Azrara, Jaafar Chbili, Anas Motii · Academic Institution · 14 Aug 2026

This research solves the problem of extracting strategic cyber threat intelligence from social media platforms, building a system called STINER to automate this process, and resulting in faster and more accurate threat intelligence. The system helps identify targeted industries, attribute attacks to ransomware groups, and assess data loss. This improves an organization's ability to respond to cyber threats.

HOW TO APPLY THIS

If you manage cybersecurity infrastructure, here is what to do: monitor social media platforms for real-time breach announcements, consider implementing automated threat intelligence tools like STINER, and review your incident response plan to ensure it incorporates social media intelligence.

View Technical Reasoning
IMPACT8/25
MATURITY5/25
MONETISATION2/25

Novelty: Conventional NER models struggle on informal social media dialect, but not a complete game-changer. Relevance: Relates to cybersecurity and threat intelligence, relevant to IT. Value: Possible for IT engineers to develop a tool for threat intelligence extraction from social media, but the description lacks specific actionability.

AI deployment⏳ Evaluating
13

SheetCompass: Hierarchical Relation Graphs for Agentic Spreadsheet Reasoning

Panjing He, Mingyue Cheng, Yucong Luo, Li Li · Academic Institution · 14 Aug 2026

This research solves the problem of automated spreadsheet reasoning by building a hierarchical relation graph called SheetCompass, which helps large language models understand complex spreadsheet structures. The result is improved ability for language models to analyze and manipulate semi-structured data in spreadsheets. This research does not directly affect cloud infrastructure management.

HOW TO APPLY THIS

Not directly applicable to IT infrastructure work, as it focuses on improving language models for spreadsheet analysis and reasoning.

View Technical Reasoning
IMPACT2/25
MATURITY10/25
MONETISATION1/25

Novelty: Agentic spreadsheet reasoning is an interesting IT angle, but it's not new (5). Relevance: Directly affects how IT engineers work with LLMs and spreadsheet reasoning (10). Value: Could be used to automate spreadsheet reasoning or propose a service to a client within 90 days (13).

NLP-performance-improvement⏳ Evaluating
13

CoRun: Padding is Simple and Efficient for Deterministic LLM Inference

Shiju Zhao, Jiacheng Yang, Qihang Chen, Junhao Hu · Academic Institution · 14 Aug 2026

This research solves the problem of inconsistent outputs in Large Language Model inference by introducing a method called CoRun, which uses padding to achieve deterministic results. The researchers built a system that enables efficient and simple padding for LLM inference. The result is a significant reduction in latency and increase in serving throughput.

HOW TO APPLY THIS

If you manage cloud infrastructure for Large Language Model applications, check your current batch processing setup and consider implementing padding to improve determinism and efficiency. This may require adjustments to your kernel configuration and tiling strategies. Not directly applicable to general IT infrastructure work, but relevant for specific LLM use cases.

View Technical Reasoning
IMPACT0/25
MATURITY3/25
MONETISATION10/25

Novelty: 3 - Observations about LLM inference are interesting for IT people. IT relevance: 0 - This is a specific NLP problem. Value: 37 - IT folks could potentially apply this to improve LLM inference performance in SaaS or on-premise setups, making it worth the score.

MLOps⏳ Evaluating
0

A Hybrid LLM-Based Framework for Automated Security Annotation Generation in Business Process Models

Md Kamrul Islam, Tiphaine Henry, Mattia Salnitri, Julius Köpke · Academic Institution · 14 Aug 2026

This research solves the problem of manually creating security annotations for business process models by building a hybrid framework that automatically generates them. The framework takes a process model and security requirements document as input and produces annotations adhering to the SecBPMN2 specification. The result is a more efficient and accurate way to incorporate security into business process models.

HOW TO APPLY THIS

If you manage business process models, here is what to do: review your current security annotation process, consider implementing an automated solution like the one presented in this research, and assess the potential benefits of increased efficiency and accuracy in your security annotations.

View Technical Reasoning
IMPACT0/25
MATURITY0/25
MONETISATION0/25

The paper presents a novel LLM-based framework for automated security annotation generation in business process models, which is directly relevant to IT engineers working with BPMN and security process models. However, the practical application and potential automation within 90 days are limited.

LLMs▶️ Video Intel✨ Evergreen Intelligence⏳ Evaluating
90

From Vibe Coding to Agentic Engineering

Andrej Karpathy · Andrej Karpathy · 06 May 2026

Analysis of the deep technical architecture, key innovations, measurable performance results, and concrete business opportunities of a large language model architecture

HOW TO APPLY THIS

Downloading and processing the internet to gather high-quality text data Representing text data as a one-dimensional sequence of symbols Designing the neural network to internalize and model patterns in the text data

View Technical Reasoning
IMPACT20/25
MATURITY22/25
MONETISATION24/25

High scores due to the model's ability to efficiently represent text data and achieve good performance in language modeling tasks

⚡ TODAY'S SIGNAL

Get ready to rewrite the language of the deaf with AI-powered sign language recognition now possible on user's devices.

AI Lab Google AI Research
1/10

Science One Framework: A verifiable autonomous research framework via Chain-of-Evidence

Google AI released Science One Framework, a verifiable autonomous research framework via Chain-of-Evidence. This development has no direct relevance to IT infrastructure.

HOW TO USE THIS

This has no specific action or use for Ahmed, but it can be noted as a development in the general field of AI.

AI Lab Microsoft Other
2/10

Looking back on Microsoft’s FY26: From AI experimentation to Frontier Transformation

Microsoft has concluded its FY26, highlighting customer adoption of AI for real-world business outcomes. This marks a shift from AI experimentation towards embedding AI at the core of businesses.

HOW TO USE THIS

Note this long-term trend in Microsoft's approach to AI and its implications for the IT landscape, particularly with Microsoft 365 and Azure.

AI Lab Microsoft Security
5/10

Rethinking security for the age of AI

Microsoft is introducing Project Perception, a new cyber stack that adapts to autonomous systems and changing security landscapes. This is a response to the evolving cost, volume, and complexity of cyber threats.

HOW TO USE THIS

While this initiative doesn't offer a direct action to take this week, consider how Project Perception's adaptive security approach aligns with or diverges from your current Google Workspace, JumpCloud, and SSO security stack, which might be beneficial to revisit in the next 90 days.

AI Lab Microsoft Research
3/10

Powering America’s Genesis Mission: Microsoft’s commitment to scientific discovery

Microsoft has announced a $60 million investment and new coordination hub for accelerating AI in science, in support of the Department of Energy's Genesis Mission. This is a long-term commitment aimed at scientific discovery and breakthroughs for the country.

HOW TO USE THIS

No direct action is required, but it indicates Microsoft's continued focus on AI innovations which may impact future IT infrastructure or tooling.

Press VentureBeat Research
5/10

Cutting RAG inference costs 6x starts with deciding what never reaches the LLM

Teams using Retrieval Augmented Generation (RAG) systems for high-stakes classification route every ambiguous case to language models, but this becomes a problem when facing audits or regulations. This architectural bet needs to be reconsidered for production-ready systems.

HOW TO USE THIS

For IT engineers managing Google Workspace or similar environments, consider reviewing your organization's data storage and retrieval practices to ensure they can withstand audits and regulatory scrutiny. Missing this means relying solely on language models which might not provide enough transparency and explainability. Consider the potential risk of relying on black-box models like LLMs.

Press TechCrunch Other
3/10

Stripe will reportedly acquire AI gateway startup OpenRouter for $7B+

Stripe plans to acquire OpenRouter, an AI gateway startup, for $7 billion. This deal has implications for Stripe's business and possibly AI gateway market.

HOW TO USE THIS

This acquisition may lead to changes in Stripe's integrations or API options, affecting Ahmed's use of tools like Google Workspace or Freshservice if they integrate with Stripe's platform. However, at this time, this is more general business news and does not have a direct action signal for Ahmed, but he should monitor Stripe's platform updates in the coming months.

Press TechCrunch Other
1/10

Why people aren’t buying Mark Zuckerberg’s AI future

Mark Zuckerberg discusses AI future on Equity podcast. Not everyone is convinced by his vision.

HOW TO USE THIS

Press TechCrunch Research
1/10

Anthropic CEO says AI backlash is ‘fundamentally a crisis of trust’

Anthropic CEO Dario Amodei defends AI's potential future, arguing that the current backlash is rooted in a 'crisis of trust'. Amodei pushes back against the notion that he's overly pessimistic about AI's potential.

HOW TO USE THIS

The current AI backlash is largely driven by concerns about AI's potential impact on society and jobs. It's essential for IT engineers to stay informed about these broader trends to understand the evolving landscape and its potential impact on their organization's technology stack.

AI Lab Hugging Face Research
3/10

State of Open Models: Summer 2026 Observations

Hugging Face published their State of Open Models: Summer 2026 Observations, highlighting trends and observations on open models. This report discusses developments in open-source AI and models.

HOW TO USE THIS

No immediate actions needed, but consider staying updated on open-source AI trends for potential future adoption or integration in existing workflows.

AI Lab Google DeepMind Model Release
6/10

Introducing Gemini 3.7 Flash

Google DeepMind has announced the launch of Gemini 3.7 Flash. This update brings improved language understanding and multimodal capabilities to the Gemini model, Google's AI-powered language model.

HOW TO USE THIS

Check your Google Workspace admin console for any Gemini 3.7 Flash updates, especially if you're using Google Workspace's AI integrations like Gmail or Google Drive. Missing this update might impact the effectiveness of AI-driven features in your organization. Google Workspace's AI features are most affected here.

AI Lab Hugging Face Research
5/10

What We Learned by Reproducing 2,200 papers from ICML

Hugging Face replicated 2,200 research papers from ICML. This exercise in reproducibility highlights the state of AI research in areas such as adversarial attacks, reinforcement learning, and more.

HOW TO USE THIS

Check your current AI research implementation (possibly in areas like adversarial attacks or reinforcement learning) to assess its alignment with industry standards and consider updating your tools to stay ahead of evolving AI research.

AI Lab OpenAI API Update
3/10

Previewing Ultrafast mode: GPT-5.6 Sol at up to 14X the speed

OpenAI has released a preview of Ultrafast mode for its GPT-5.6 Sol, which provides up to 14 times the speed of the current service. This allows for faster and more efficient processing of AI tasks, but its impact on IT infrastructure is still unknown.

HOW TO USE THIS

Note this, revisit in 90 days: As IT engineers, you may want to monitor OpenAI API service tier updates for potential impacts on your workflow, such as changes in pricing, availability, or functionality. Although Ultrafast mode doesn't directly affect your tools, it's worth keeping an eye on for any subsequent innovations.

AI Lab OpenAI Research
2/10

The builder’s guide to GPT‑5.6

OpenAI has released GPT-5.6, a guide for builders, which includes a Responses API. This guide helps startups build AI agents more efficiently.

HOW TO USE THIS

There is no direct impact on IT infrastructure, but considering AI-driven automation can bring opportunities for IT efficiency, explore the Responses API for potential integration with existing tools.

AI Lab Hugging Face Tools
2/10

Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets

Hugging Face has launched one-stop-shop Strands Agents, allowing users to record, train, and deploy models without leaving the platform. This integration streamlines the entire AI development process.

HOW TO USE THIS

Watch the Hugging Face Strands Agents for potential impact on MLOps workflows across SaaS offerings like Google Workspace or custom-built platforms, especially if using Hugging Face transformers or models.

AI Lab OpenAI Other
1/10

OpenAI appoints Dali Rajic as Chief Revenue Officer

OpenAI appointed Dali Rajic as its new Chief Revenue Officer. This leadership move is significant for OpenAI's revenue strategy, potentially impacting businesses that use AI.

HOW TO USE THIS

No high-value action for IT engineers here; note the personnel move for potential future implications on pricing, adoption, or business model of AI technologies that use OpenAI APIs.

Consulting MIT Sloan Other
0/10

Why Water Management Is a Strategic Concern

There is no specific AI-related news item. The article discusses the concern of water management as a strategic issue.

HOW TO USE THIS

AI Lab Google DeepMind Tools
7/10

Putting sign language AI into users’ hands

Google DeepMind has introduced sign-language-to-text (SL2T), a breakthrough model for sign language features on Google products. This is particularly relevant for IT engineers managing accessibility features in their organization.

HOW TO USE THIS

Check if your organization can integrate or leverage SL2T features into existing Google products to enhance accessibility for Deaf and hard of hearing users, potentially improving overall user experience and engagement.

AI Lab Microsoft Research Research
3/10

MindTopo reveals VLMs’ spatial reasoning abilities

MindTopo, a benchmarking platform, reveals that Visual Language Models (VLMs) can understand spatial relationships, as demonstrated by their performance on a path, fence, and knot task. This achievement sets a new benchmark for spatial reasoning and planning.

HOW TO USE THIS

While this achievement has broader implications for AI development, it doesn't directly impact existing IT infrastructure. However, it's worth monitoring as advancements in spatial reasoning could lead to more sophisticated AI tools in the future.

AI Lab Google AI Research
3/10

Empty shelves or lost keys? Recall is the bottleneck for parametric factuality

Google AI published a paper discussing the bottleneck of parametric factuality in generative models, specifically recall. This issue can lead to incomplete or inaccurate information in responses.

HOW TO USE THIS

AI Lab Microsoft Research Research
2/10

Introducing CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement

Microsoft Research has introduced CARE-X, a unified approach for chest X-ray interpretation combining flexible reasoning, calibrated predictions, and measurement-based tools.

HOW TO USE THIS

Check your Google Workspace Admin Console for potential adoption of similar AI-powered tools to augment diagnostic interpretation of medical imaging.

Consulting MIT Sloan Other
2/10

How to End Things Well

HOW TO USE THIS

This article's focus on endings in organizational life might inform IT engineers on how to properly sunset or decommission IT resources and assets, though it doesn't directly relate to AI.

AI Lab Google AI Research
1/10

Advancing AMIE towards expert-level audio-visual clinical consultations

Google AI has advanced its Audio-Visual Interaction Engine (AMIE) towards expert-level audio-visual clinical consultations. This improvement enables more accurate and efficient analysis of patient conditions.

HOW TO USE THIS

Consulting MIT Sloan Other
1/10

How to Avoid Innovation One-Hit Wonders

This article discusses strategies for managing innovation, highlighting success patterns and how they can be adapted for future projects. However, innovation one-hit wonders can occur due to an inability to replicate past success.

HOW TO USE THIS

AI Lab Google DeepMind Model Release
3/10

WeatherNext: AI model achieves breakthrough in forecasting cyclones

Google DeepMind has achieved a breakthrough in forecasting cyclones with its WeatherNext AI model. This advancement does not directly impact IT infrastructure, but it could lead to the development of more sophisticated AI tools for various industries, including IT.

HOW TO USE THIS

AI Lab Microsoft Research Research
5/10

Orchard: An open framework for scalable agentic AI

Microsoft Research has released Orchard, an open-source framework for training and evaluating AI agents across task types, reducing complexity while supporting strong performance from smaller models.

HOW TO USE THIS

While not directly affecting your IT stack, note that advancements in AI frameworks can indirectly impact your organization's AI tooling and workflows. Review recent developments in AI research and assess potential long-term implications for your company.

2026-08-17
9 items
Knowing When to Stop: Bayesian Optimal Stopping for LLM EvalAgentRewind: Recoverable Execution for Long-Horizon LLM AgenFinding Vulnerabilities via LLM-Augmented Semantics-Aware Ty
2026-08-16
1 items
Spatial Memory Agent: Experience-Grounded Procedure Memory f
2026-08-15
6 items
A Gateway Architecture for Enterprise MCP Authentication: UnAgentSOC: A Multi-Layer Agentic AI Framework for Security OpLLM-Assisted Dynamic Threat Analysis for Attacker-Reachable
2026-08-14
8 items
YAVIN: A Unified Architecture for Secure Edge Processing in GUIDE: Governed Unified Intelligence for Document-to-ArtifacPIPES: Securing Agent Perception with Provenance and Priors
2026-08-13
10 items
The Role Specialization Model (RSM): Coordinating LLM-Based Rethinking Agent Security as a Networking ProblemBeyond Trial-and-Error: Agentic Optimization for Image-to-Vi
2026-08-12
4 items
Software Engineering for and with GUI AgentSimilarity Gates Approve Reversals: A Validity Audit of EmbeElasticBack: Stealthy Conditional Backdoor in LLM-Agent Skil
2026-08-11
4 items
Defining Decentralization: An Ontological PerspectiveGenerative AI for Encrypted Traffic Analysis: Synthetic DataSWE-Bench ProMax: Benchmarking Agents on Large-Scale Multili
2026-08-10
2 items
Structure-Aware Semantic Chunking with Title-Chain Prefixes:SyncSBC: Decentralized Swarm Behavior Prediction for Synchro
2026-08-09
9 items
PICopilot: An LLM-based Agentic Framework for Assisting PhotOn-Policy Self-Distillation without Any SupervisionTytan: Interactive Neurosymbolic Construction of Analytic Se
2026-08-08
4 items
Evaluating LLM Trade-offs for Enterprise Automation: LessonsFormBharo: Designing and Evaluating a Voice Agent for ConverPost-Hoc Trajectory-Risk Certification for Modular LLM-Based
2026-08-07
9 items
Benchmarking and Enhancing LLMs for Rule-Intensive Review ofLearning Globally Reusable Skills for Coding AgentsTRAJDEBUG: Tracing Error Lifecycle to Identify Critical Fail
2026-08-06
13 items
WeClawArena: An Auditable Sandbox and Benchmark for Cross-UsSparseDitto: Customizing GPU Kernels for Different Sparsity CURATE: Leveraging LLM Agents to Compose, Catalog, and Deplo
2026-08-05
9 items
Harness-R1: Learning to Edit Executable Runtime Harnesses frFormal Verification of Agentic Systems over Operational DataA Security-Oriented Lifecycle Model for Large Language Model
2026-08-04
10 items
Securing Agentic AI: From Per-Action Checks to Trajectory AsAdversarial Attacks in Multi-Agent LLM Pipelines: Unveiling Why Formal Monitors Fail: Attack Distribution Entropy as a C
2026-08-03
7 items
IDP AutoOpt: Agent-Driven Optimization of Document ProcessinStop Shipping AI Agents on Faith: Capability Is Not ProductiMerchantBench: Benchmarking LLM Agents for Long-Term Coheren
2026-08-02
2 items
AIGen: Automating AI Bill of Materials Generation Through HyWhen Derived Measurements Mislead: Quantifying and Mitigatin
2026-08-01
6 items
PAUSE: A User-Centric Benchmark for Personal AI Assistants iStealthBench: Measuring Operational Stealth in Autonomous OfCoGate: Confidence-Gated Co-Decoding for Secure Code Generat
2026-07-31
6 items
Cybersecurity Detection Classification with Reasoning-enableRoboBRIDGE: A Modular Framework for Bridging Policies to RobORCA-bench: How Ready Are Language Model Agents for Oncall?
2026-07-30
6 items
Towards an Agent Operating System - Lessons from Classical aTurboVLA: Real-Time Vision-Language-Action Model at 32 Hz onImproving Item Discoverability in e-Commerce Search via Rela
2026-07-29
12 items
SkillGate: Cost Efficient Runtime Malicious Skill File DetecAgent Skills Matter: Inferring Proprietary Skills from ExecuLLM4OSC: Profile-Bound Natural Language Control with Determi
2026-07-28
9 items
TRACE-ROUTER: Task-Consistent and Adaptive Online Routing foA corrective agentic hybrid RAG and an operations-grounded eMMOE: Modernizing Diffusion Transformers with Efficient Expe
2026-07-27
10 items
A Self-Calibrating Agentic AI Framework for Autonomous Edge TRACE-ROUTER: Task-Consistent and Adaptive Online Routing foLearning on the Job: Continual Learning from Deployment Feed
2026-07-26
3 items
VoLN: Vision-Only Long-Horizon Navigation---Paradigm, BenchmFrontier Financial Judgement: Can agents tell what might movGuardrails as Scapegoats: Auditing Unfaithful Safety Refusal
2026-07-25
9 items
The Ethics of Autonomous AI Agents for Offensive SecurityHiMe: Real-Time Self-Hosted Personal Agent Platform for HealFrom Resource Flow to Executable Tests: Petri-Net-Guided LLM
2026-07-24
2 items
ABot-World-0: Infinite Interactive World Rollout on a SingleThinkink: 2D Spatial Ink-native Interaction with LLMs
2026-07-23
9 items
PyroDash: Cost-Efficient Token-Level Small-Large Language MoThe Blessing of Dimensionality: How Near-Orthogonality in HiAgents in the Wild: Where Research Meets Deployment
2026-07-22
9 items
LLM Detection as an Intervention: Downstream Impact under StCross-Agent Campaign Attribution: Linking Asynchronous AttacAI Prototyper: A Figma Plugin for Decomposition-Based GUI Pr
2026-07-21
14 items
An Explicit World Model Based on Data-First Ontology: DaoQL GARAGE: Characterizing the Automation Boundary in LLM-based ZifaMem: Structured Memory for Persona, Preference, and Emot
2026-07-20
1 items
Cache-Aware Prompt Compression:A Two-Tier Cost Model for LLM
2026-07-19
6 items
CAVA: Canonical Action Verification and Attestation for RuntCopy-on-Write Scoring: Application-Specific Agent EvaluationRubrics on Trial: Evolving Rubrics from a Single Query via S
2026-08-17
25 items
Putting sign language AI into users’ handsIntroducing Gemini 3.7 FlashRethinking security for the age of AI