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After months of heads-down grinding, I’m proud to share that the @GPTZeroAI team has released the world’s most accurate AI detection model, …

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After months of heads-down grinding, I’m proud to share that the @GPTZeroAI team has released the world’s most accurate AI detection model, GPTZero 4o. It’s called 4o because there are four zeros: we

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Agent Factory recap: Agent harnesses, shifting left, and autonomous coding

model-releasesgoogle-cloud-ai

In this episode of The Agent Factory, we explore the reality of building with autonomous agents alongside Ryan Lopopolo, a software engineer at Google Cloud and the person who coined the term agent ha

AI-Driven Neural Surrogates for In Silico Design of Cognitive-Affective Neuromodulation Targets

arXiv:2609.27729v1 Announce Type: cross Abstract: In neuropsychiatry, the primary goal is often not only to decode brain activity but to change it, for example to lessen a negative affective bias or a

AnchorReasoning: A Visual Grounding and Causal Reasoning Dataset in Long-Tail Autonomous Driving Scenarios

arXiv:2609.28366v1 Announce Type: cross Abstract: Vision-language models (VLMs) offer a promising approach to long-tail autonomous driving, but existing driving datasets provide limited supervision fo

local-aiarxiv-cs-ai

AraGenre 2026: A Hierarchical Definition-Guided Arabic Genre Classification Shared Task

arXiv:2609.27387v1 Announce Type: new Abstract: AraGenre is a shared task on hierarchical, definition-guided Arabic genre classification, motivated by the limited availability of annotated data in Ara

Automated Extraction of Records of Processing Activities (RoPA) Using Hybrid RAG and Locally Deployed Large Language Models

arXiv:2609.27359v1 Announce Type: new Abstract: Vietnam's Personal Data Protection Law (Law No. 91/2025/QH15) and Decree No. 356/2025/ND-CP, effective January 1, 2026, require organizations to establi

Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation

arXiv:2609.27394v1 Announce Type: cross Abstract: Automotive spinning FMCW radar provides dense, 360^irc sensing and remains reliable under poor illumination and adverse weather, making it well-suited

Backdoors in Learning-Based Industrial Robotic Arm Manipulation: An Empirical Security Study

arXiv:2609.26868v1 Announce Type: new Abstract: Learning-based models (e.g., visuomotor and Vision-Language-Action (VLA)) are increasingly explored for industrial robotic manipulation, where model pre

researcharxiv-cs-ro

Banana Kick: Response-Informed Skill Evolution for Humanoid Soccer

arXiv:2609.27269v1 Announce Type: new Abstract: Humanoid kicking requires coordinated whole-body motion and precise contact, while a banana kick demands contact mechanics that generate ball spin and a

safetyarxiv-cs-ro

BEE: Intervention-Adaptive Real-World Reinforcement Learning with Vision-Language-Action Models

arXiv:2609.27450v1 Announce Type: cross Abstract: Vision-language-action (VLA) models handle long-horizon manipulation, yet success hinges on a few precision-critical phases where millimeter-scale err

Behavior-Aligned Action Tokenization for Robot Policy Learning

arXiv:2609.27513v1 Announce Type: new Abstract: Autoregressive robot policies learn continuous control by predicting discrete action tokens from observations. Different tasks often share local motions

safetyarxiv-cs-ro

Benchmarking Text-to-SQL under Role-Based Access Control

arXiv:2607.22115v2 Announce Type: replace-cross Abstract: Given a database S and a natural language question Q, text-to-SQL systems aim to generate an SQL query that correctly answers Q when executed

Beyond Unsafe Detection: Counterfactually Anchored Evidence Attribution for Multi-Turn LLM Safety Failures

arXiv:2609.27773v1 Announce Type: cross Abstract: As Large Language Models (LLMs) move from conversational assistants to advanced agentic systems, guardrail failures can convert adversarial intents in

Binary Classification from Coupled Pairwise Labels

arXiv:2603.19713v2 Announce Type: replace Abstract: Even when it is difficult to assign absolute class labels to individual instances, relational information may still be available, such as whether tw

researcharxiv-cs-lg

Hardware

BladeMaster: Real-Time Robotic Cutting Simulation with Online-Generated Persistent Discontinuities

arXiv:2609.27342v1 Announce Type: new Abstract: Cutting changes both the shape and topology of deformable objects, making accurate simulation challenging for robotic manipulation. A simulator must tra

hardwarearxiv-cs-ro

BronchoTop: Bronchoscopy Navigation via RGB-Only Topological Localization

arXiv:2609.28328v1 Announce Type: new Abstract: Accurate localization of the bronchoscope within the bronchial tree is essential for clinicians to be able to reach target lesions, perform biopsies and

local-aiarxiv-cs-cv

Can One Adapted Model Do It All? Fine-Tuning Strategy Selection for Customer Support LLMs

arXiv:2609.27262v1 Announce Type: new Abstract: Production customer-support systems often require LLMs to support multiple skills, such as intent classification, question answering, summarization, or

CasCVS-Net: A Staged Multi-Task Cascade for Critical View of Safety Assessment

arXiv:2609.27681v1 Announce Type: new Abstract: Automated assessment of the Critical View of Safety (CVS) in laparoscopic cholecystectomy requires both recognition of the three CVS criteria and anatom

safetyarxiv-cs-cv

Categorical Internalisation of Environmental Groupoids for Generalisable POMDP Solving

arXiv:2609.27745v1 Announce Type: new Abstract: This paper advocates category theory as a practical framework for structuring and improving rein- forcement learning in high-dimensional, partially obse

Causal Tracing of Audio-Text Fusion in Large Audio Language Models

arXiv:2603.13768v2 Announce Type: replace-cross Abstract: Despite the strong performance of large audio language models (LALMs) in various tasks, exactly how and where they integrate acoustic features

ChronosAttack: Adversarial Tool Scheduling Attacks on LLM Agents

model-releasesarxiv-cs-lg

arXiv:2609.27857v1 Announce Type: cross Abstract: Large language model (LLM) agents often process external tool responses as they arrive, making response timing part of the decision process. We introd

Combining LLMs and Genetic Search for ARC-AGI-2

arXiv:2609.27242v1 Announce Type: cross Abstract: LLMs can generate programs for ARC-AGI-2 tasks, but the provided compute only allows a small number of attempts to generate, debug and validate soluti

researcharxiv-cs-ai

Contact-Implicit Stein Projected ADMM for Discovery of Diverse Contact-Rich Manipulation Strategies

arXiv:2609.28299v1 Announce Type: new Abstract: Contact-implicit trajectory optimization formulates contact-rich manipulation as a single constrained program; however, that single program run collapse

local-aiarxiv-cs-ro

Context-Continuous Preference Learning for Exoskeleton Personalization

arXiv:2609.28427v1 Announce Type: new Abstract: Personalizing exoskeleton assistance across operating conditions is constrained by the time and physical effort required to collect user feedback. We ex

researcharxiv-cs-lg

CoRe-WAM: Correspondence-Aligned Temporal Residuals for World Action Models

model-releasesarxiv-cs-ro

arXiv:2609.27314v1 Announce Type: new Abstract: Comparing current and past observations helps robots understand scene changes and select subsequent actions during manipulation. However, comparing visu

Counterfactual Constraint-Conditioned On-Policy Distillation for Multi-Constraint Instruction Following

model-releasesarxiv-cs-lg

arXiv:2609.27421v1 Announce Type: new Abstract: Multi-constraint instruction following requires a model to respond to a query under many simultaneously active constraints. Even strong instruction-tune

Cross-Modal Contrastive Learning from Histopathology and CT for Automated Renal Cell Carcinoma Grading

arXiv:2609.26920v1 Announce Type: cross Abstract: Background: Clear cell renal cell carcinoma (ccRCC) exhibits substantial clinical heterogeneity, and accurate grade assessment is essential for risk s

Crossflow: Prefill-Decode Elasticity for Agentic LLM Serving

arXiv:2609.27085v1 Announce Type: cross Abstract: As serving capacity demand surpasses that of training, serving efficiency becomes increasingly important. Prefill-decode (P/D) disaggregation improves

Damnatio Memoriae: Adversarially and Selectively Forgetting Identities in the Embedding Space of Face Recognition Models

arXiv:2609.27115v1 Announce Type: new Abstract: A face recognition model links two images of a person recorded on separate occasions when their embedding similarity exceeds an operating threshold. We

researcharxiv-cs-cv

Delegated Misalignment: How Multi-Agent Structures Amplify LLM Safety Risks

arXiv:2609.27900v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in multi-agent systems where a principal agent decomposes tasks and delegates them to subordinate

Design and Modeling of a Single-Port Three-Arm Robotic Tool for Minimally Invasive Neurosurgery

arXiv:2609.27099v1 Announce Type: new Abstract: Surgical robots require highly dexterous and compact robotic systems capable of operating effectively within confined anatomical spaces. However, due to

researcharxiv-cs-ro

Discovery of fully efficient fault indicators along a data-based diagnosis process

arXiv:2609.28087v1 Announce Type: new Abstract: The integration of model-based and data-driven paradigms provides a powerful framework for fault diagnosis by combining the interpretability of analytic

Tutorials

Discrete Diffusion Models via Evolving Variational Autoregressive Networks

arXiv:2609.27306v1 Announce Type: new Abstract: Conventional score-based diffusion models learn scores without representing normalized densities, whereas tractable normalized models support both sampl

tutorialsarxiv-cs-lg

Distilling Sequential Computation in Transformer Language Models

arXiv:2609.27233v1 Announce Type: new Abstract: Transformer language models process sequences token by token in an autoregressive manner, making growing contexts increasingly expensive. Yet many adjac

researcharxiv-cs-cl

Do We Need Complex Topology Control? Distinct-Peer Random Routing Improves Cost-Efficiency in Sparse Multi-Agent Debate

arXiv:2609.27150v1 Announce Type: new Abstract: Multi-agent debate (MAD) has emerged as a promising paradigm for improving the reasoning accuracy of large language models (LLMs) through iterative peer

DRSR: Learning Set-Level Deletion Risk for Efficient Long-Horizon Agents

arXiv:2609.27276v1 Announce Type: new Abstract: Long-horizon language-model agents accumulate reasoning traces, tool exchanges, and observations whose relevance changes with the current decision. Exis

Applications

DualStabSleepNet: A Dual-Domain Diffusion Stabilization Network for Robust Sleep Staging

arXiv:2609.27793v1 Announce Type: new Abstract: Existing deep learning approaches for automatic sleep staging suffer from limited robustness under heterogeneous recording conditions, where non-station

applicationsarxiv-cs-cv

EA-WM: Event-Aware Generative World Model with Structured Kinematic-to-Visual Action Fields

arXiv:2605.06192v2 Announce Type: replace-cross Abstract: Pretrained video diffusion models provide powerful spatiotemporal generative priors, making them a natural foundation for robotic world models

Hardware

EBRL: Asynchronous Embodied RL by Multi-Grained Resource Management

arXiv:2609.27547v1 Announce Type: new Abstract: Embodied reinforcement learning (RL) improves model capabilities with a pipeline of environment simulation, action generation, and model updates. These

hardwarearxiv-cs-lg

EduBehaviors: Assertion-based Schemas for Auditable Coding of Educational Dialogues

arXiv:2609.27043v1 Announce Type: new Abstract: Large language models have allowed the rapid deployment of pedagogical annotations corresponding to constructs of interest, allowing a natural language

researcharxiv-cs-cl

EMA: Elastic and Performance Transparent Memory Across GPUs

arXiv:2609.27040v1 Announce Type: cross Abstract: Multi-GPU servers have become the standard building block of modern data centers, providing aggregated capacity through high-bandwidth interconnects.

local-aiarxiv-cs-ai

EnSIMem: Entity-Structured Indexing for Long-Term Agent Memory

arXiv:2609.27279v1 Announce Type: new Abstract: An agent that interacts with users over long periods must recall facts, preferences, events, and changes from a continuously growing interaction history

Escaping Python Dependency Hell: A Hybrid Replay-and-Repair Pipeline for Python Dependency Resolution

arXiv:2609.26952v1 Announce Type: new Abstract: Dependency conflicts in Python ecosystems arise from incompatible version constraints, missing packages, and undocumented compatibility relationships, c

EviStreams: Human-in-the-Loop AI Data Extraction for Systematic Reviews in Medicine

arXiv:2609.27418v1 Announce Type: new Abstract: Systematic reviews underpin clinical guidelines, yet their data-extraction step is a major expert-labor bottleneck bound by a protocolized workflow: two

Evolutionary Stability Does Not Guarantee Learning Accessibility: A Multi-Agent Reinforcement Learning Perspective on Cooperation Emergence

arXiv:2609.27664v1 Announce Type: new Abstract: Cooperation emergence is a central problem in multi-agent systems because decentralized agents must coordinate while adapting to the changing behavior o

Evolving Inspectable O-RAN Slicing xApps with LLMs

arXiv:2609.27337v1 Announce Type: cross Abstract: Open RAN (O-RAN) slicing xApps must adapt resource allocations to changing channel conditions and traffic demands while meeting service-level agreemen

researcharxiv-cs-ai

FairTest: Search-Based Fairness Testing for Multi-Agent Reinforcement Learning Systems

arXiv:2609.27309v1 Announce Type: cross Abstract: Multi-agent Reinforcement Learning (MARL) trains a team of agents that share one environment and learn their policies together. Training maximizes the

safetyarxiv-cs-lg

FFM-CP: Cross-Backbone Fusion of Vision-Language Foundation Models for Few-Shot Computational Pathology

arXiv:2609.27710v1 Announce Type: new Abstract: Pathology vision-language foundation models vary in performance across diseases and tasks, with no single model consistently performing best. The high c

safetyarxiv-cs-cv