Search: “engineering”

Resilience Matters for Embodied Agents System: New Metrics, Systematic Evaluation, and Optimization

arXiv:2608.23839v1 Announce Type: cross Abstract: Embodied Agents System (EAS) are increasingly deployed in open-world physical domains, where reliability directly dictates deployment quality and huma

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Agents

Review of Explainable Decision Support and Adaptive Human-Machine Interfaces for Automation Transparency in Maritime Autonomous Surface Ships

DGX agent

arXiv:2509.15959v2 Announce Type: replace-cross Abstract: Autonomous navigation in maritime domains is accelerating alongside advances in artificial intelligence, sensing, and connectivity. Opaque dec

agentsarxiv-cs-ai

26 Aug 2026

StepGuard: Learning Step-Level Guardrails with Scalable Supervision and Safety-Utility Balancing

arXiv:2608.24777v1 Announce Type: new Abstract: LLM-based agents can interact with external environments through tool invocation, but this capability also introduces security risks such as file modifi

TrustShiftProbe: Characterizing, Benchmarking, and Defending Staged Trust Attacks on MCP Servers

arXiv:2608.23763v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has emerged as the standard layer connecting Large Language Model agents to external tool backends. This openness int

Want to test how good GLM-5.3-Flash is? I have been finding it useful for visual explainers using /eli5. Try it with Pi or Hermes Agent in o…

Want to test how good GLM-5.3-Flash is? I have been finding it useful for visual explainers using /eli5. Try it with Pi or Hermes Agent in our new agent playground: https://academy.dair.ai/dashboard/p

model-releasesdair-ai--x

We’re excited to announce that 𝗛𝗮𝗿𝗿𝗶𝘀𝗼𝗻 𝗖𝗵𝗮𝘀𝗲 @hwchase17, Co-Founder & CEO of @LangChain, will be speaking at VapiCon 2026! 🎙️…

We’re excited to announce that 𝗛𝗮𝗿𝗿𝗶𝘀𝗼𝗻 𝗖𝗵𝗮𝘀𝗲 @hwchase17, Co-Founder & CEO of @LangChain, will be speaking at VapiCon 2026! 🎙️ Harrison co-founded LangChain with the goal of making it easier to use LL

agentsharrison-chase--x

Local Ai

When Similarity Is Interaction-Driven: Quantum Kernels for Regime-Sensitive Learning

arXiv:2608.24631v1 Announce Type: cross Abstract: Similarity in many decision systems is governed not by distance alone but by interactions among variables. In fraud and anomaly detection, small local

local-aiarxiv-cs-lg

Your chance to start building AI agents from the absolute basics

Have you been hearing a lot about 'AI agents' lately but aren't sure how to actually start building them? You don't need a background in machine learning or years of software experience to get started

agentsgoogle-cloud-ai

35B-A3B tool calling benchmark: Original Qwen vs. KAT Coder, Ornith and Tiel-Coder

With hopes of a Qwen3.8-35B-A3B release now mostly dashed, many people including myself are looking at fine-tunes and other variants of Qwen3.6-35B-A3B to run on VRAM-limited hardware. I decided to tr

A Physical Response-and-Memory Model for Muon Optimization

arXiv:2608.22994v1 Announce Type: cross Abstract: Training large language models is costly. How low a loss the same compute can ultimately reach depends on how each step's gradient is converted into a

Hardware

Adversarial Entropy Inflation Against Gumbel-Based Inference Verification

arXiv:2608.23375v1 Announce Type: cross Abstract: Gumbel-based inference verification bounds LLM weight exfiltration by only forgiving token choices that plausibly arise from honest GPU nondeterminism

hardwarearxiv-cs-ai

Agentic-Kube: A Graph-Enhanced Multi-Agent Reinforcement Learning Framework for Multi-Objective Kubernetes Scheduling

arXiv:2603.12031v3 Announce Type: replace-cross Abstract: Cloud-native container orchestration requires resource schedulers capable of balancing infrastructure expenditure, fault resilience, and node

safetyarxiv-cs-lg

Agentic Security: A Systematization of Tools, Failure Modes, and Design Laws for LLM-Driven Penetration Testing

arXiv:2608.21423v1 Announce Type: cross Abstract: Agentic security uses large-language-model (LLM) agents to plan, dispatch, and interpret security tools. As these systems move from demonstrations to

Hardware

AI factories enter the execution era as Cisco and Nvidia push rack-scale systems into production

The artificial intelligence infrastructure market is crossing an important threshold. The conversation is shifting from acquiring graphics processing units to building complete AI factories that can g

hardwaresiliconangle

Analyzing and Mitigating Cross-Lingual Degradation in Multilingual Medical VQA

arXiv:2608.22363v1 Announce Type: new Abstract: Medical visual question answering (VQA) is a crucial task in clinical AI, yet its evaluation has so far centered almost exclusively on English, limiting

Local Ai

Apple unveils a more powerful Mac mini featuring the all-new M6 and M5 Pro

'A 12-core GPU, also with two more cores than before, now includes Neural Accelerators in each core for the first time on Mac mini, resulting in up to 4x faster AI performance and 2x faster graphics t

local-air-localllama

AUDITA: certified auditing and causal attribution of adverse outcomes in autonomous multi-agent systems

arXiv:2608.22160v1 Announce Type: new Abstract: Physical automation is scaling toward fleets of embodied machines commanded by an AI brain. Early deployments already run factories and warehouses at pr

Bringing gVisor sandboxes to distributed Ray clusters

The reinforcement learning (RL) ecosystem is rapidly adopting Ray as the unified compute runtime for complex post-training workflows. Across Google Cloud, we see customers using Ray for workloads rang

agentsgoogle-cloud-ai

Can Coding Agents Build Robust Baselines? A Skill-Based Approach for Automating the Medical Imaging Model-Development Pipeline

arXiv:2608.23336v1 Announce Type: new Abstract: Developing competitive deep learning baselines for medical imaging remains a highly iterative process requiring literature review, implementation, exper

agentsarxiv-cs-cv

Data-Driven Dynamic Algorithm Dispatch with Large Language Models

arXiv:2608.21584v1 Announce Type: new Abstract: We introduce a large language model (LLM)-driven approach for generating dynamic algorithmic dispatch heuristics in high-performance linear algebra. By

DeepSAGE: Stage-Aware Reinforcement Learning for Structured CBT Counseling Dialogue

arXiv:2608.22615v1 Announce Type: new Abstract: Large Language Model (LLM)-based counseling agents can generate fluent and supportive responses, but they often lack the structured, goal-directed progr

Dynamic Cogeneration of Bug Reproduction Test in Agentic Program Repair

arXiv:2601.19066v3 Announce Type: replace-cross Abstract: Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix gen

Tutorials

EchoWM: Open and Enterable Omnimodal World Models

arXiv:2608.23189v1 Announce Type: new Abstract: We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, e

tutorialsarxiv-cs-cv

EG-ARSA: An Expert-Grounded Open Model for Visual Road Safety Auditing in Low-Resource Settings

arXiv:2608.23563v1 Announce Type: cross Abstract: Road traffic injuries remain a major challenge in low- and middle-income countries, where proactive road safety auditing is limited by incomplete cras

Future Querying: Can LLMs Serve as Implicit Medical World Models?

arXiv:2608.23248v1 Announce Type: cross Abstract: Traditional clinical prediction models rely on task-specific pipelines and curated, structured data, which scale poorly and underutilize unstructured

researcharxiv-cs-ai

Graph Representation Learning of Lightweight IoT Ciphers

arXiv:2608.23054v1 Announce Type: new Abstract: SIMON and SIMECK belong to a family of Lightweight Cryptographic Algorithms (LCAs) based on the Feistel block cipher, designed for Internet of Things (I

researcharxiv-cs-lg

Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems

arXiv:2606.17443v2 Announce Type: replace Abstract: Large language models (LLMs) are becoming a major way for consumers to find products, but we do not yet understand how brands compete in this new ch

Iteration Without Elaboration: A Simple ReAct Architecture Suffices for Text-to-SQL Generation

arXiv:2608.22651v1 Announce Type: new Abstract: Modern text-to-SQL systems have become increasingly elaborate, relying on schema-linking modules, retrieval-augmented prompting, candidate generation, a

researcharxiv-cs-cl

KellyBoost: Growth-Optimal Portfolio Construction with Gradient-Boosted Trees

arXiv:2608.23393v1 Announce Type: cross Abstract: KellyBoost is a single multi-output XGBoost model whose softmax output is the portfolio: with y the vector of per-asset holding-period returns, the tr

researcharxiv-cs-lg

Learning Reduced-Order Dynamics with Singularity via Latent-Augmented Neural Ordinary Differential Equations

arXiv:2608.22142v1 Announce Type: new Abstract: This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented

researcharxiv-cs-lg

Mac Studio M5 Max Cost Analysis

At $10k, you could get - 6.2B tokens with Qwen 3.8 Max (Qwen Pro plan) - 5.7B tokens with DeepSeek V4 Pro OpenRouter - 100B tokens with DeepSeek V4 Flash OpenRouter As a firm believer of local inferen

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM

arXiv:2509.20067v5 Announce Type: replace Abstract: Large language models (LLMs) have shown promise in supporting medical diagnosis, with prompting-based methods offering a flexible and deployable mea

MCP-Universe RL: A Framework for Training MCP Tool-Use Agents via Reinforcement Learning

arXiv:2608.22167v1 Announce Type: new Abstract: Reinforcement learning (RL) has become an effective way to improve the tool-use ability of large language models (LLMs), but most existing RL frameworks

MetaCaster: Meta-Harness-Optimized Agent for End-to-End Few-Shot Learning of Lightweight Time Series Forecasters

arXiv:2608.23473v1 Announce Type: cross Abstract: Time series forecasting (TSF) is evolving toward multimodal and agentic settings, yet using foundation models remains uneconomical in resource-constra

Molecular LLM Agents: From Architectural Design to Scientific Autonomy

arXiv:2608.23104v1 Announce Type: cross Abstract: Molecular science represents an important frontier for LLM-based agents. Unlike general agents that mainly operate over natural language, code, or web

New: Llama.cpp adaptive speculation for faster inference

We have been working on some performance optimisations for Qwen3.8 and other models. The main new feature that we introduced is adaptive speculation for Llama.cpp What is it? MTP and DFlash work well

Now introducing Gemini Enterprise for Legal

model-releasesgoogle-cloud-ai

Few professions are as exacting as the practice of law. A team reviewing a contract or building a case works inside strictly privileged information, firm-specific playbooks, and a body of law that cha

On the Threat Model of Weird Generalization and Emergent Misalignment

arXiv:2608.23476v1 Announce Type: new Abstract: Narrow fine-tuning on small, domain-specific datasets can produce broad and surprising changes in model behavior-a phenomenon called weird generalizatio

researcharxiv-cs-cl

One Polluted Page Is Enough: Evaluating Web Content Pollution in LLM Recommenders

arXiv:2606.13610v2 Announce Type: replace-cross Abstract: Search-augmented LLMs increasingly mediate everyday consumer recommendations by retrieving live web content. This creates a new risk: LLM reco

One Request, Multiple Experts: LLM Orchestrates Domain Specific Models via Adaptive Task Routing

arXiv:2511.12484v2 Announce Type: replace-cross Abstract: With the integration of massive distributed energy resources and the widespread participation of novel market entities, the operation of activ

Perturb the Thought, Not the Pixels: Latent-Space Rollout Diversification for Reinforcement Learning of Vision-Language Models

arXiv:2608.21595v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning ability of vision-language models (VLMs), and diversifying the rollouts wit

safetyarxiv-cs-cv

PsychJail: Exploring Psychological Jailbreaks via Multi-Turn Persuasion of LLM Policies

arXiv:2608.23028v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in education, healthcare, policy advising, and other interactive settings, where users engage the

Qwen 4 architecture: What do we know?

My best bet is the embedding-offloaded linear where the 51b n-grams track semantics and context, like 3.8 with its loss of real world knowledge bolted back on. Otherwise? Sparse full-attention with de

Local Ai

Read, Write, Relax: Why Neural PDE Surrogates Need Both Global and Local Processing

arXiv:2608.21677v1 Announce Type: cross Abstract: Recent mesh-based simulation advances have, in no small part, relied on neural surrogates of two distinct families: global models that route informati

local-aiarxiv-cs-ai

Register Shifts Break LLM Safety: A Bengali Benchmark with Culturally Grounded Harms

arXiv:2608.22335v1 Announce Type: cross Abstract: Bengali is the seventh-most-spoken language globally, yet LLM safety evaluation remains overwhelmingly English-centric. We introduce BanglaSafe, a ben

Applications

ReWorld: An Interactive World Model with Long-Horizon Memory

arXiv:2608.23565v1 Announce Type: new Abstract: An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control

applicationsarxiv-cs-ai

Right-Sizing LLM-Agent Decomposition in VAT Determination: A Pilot Controlled Sweep

arXiv:2608.23395v1 Announce Type: cross Abstract: Recent LLM-agent systems make conflicting design bets: decompose work across many narrow agents, or use one strong tool-using agent. This pilot studie

Spectral Pre-Filtering for Context-Adaptive Sensor Fusion: A Four-Role FFT-GDCB Integration for High-Stakes Decision Systems

arXiv:2608.22023v1 Announce Type: new Abstract: Context-adaptive Kalman filters calibrate their noise covariance matrices Q and R from innovation residuals via online regression. When the underlying s

agentsarxiv-cs-lg