applications

Most startups celebrate their first couple million of revenue. @FactoryAI gave it back. They didn’t have to. They chose to. They decided tha…

applicationssonya-huang--x

Most startups celebrate their first couple million of revenue. @FactoryAI gave it back. They didn’t have to. They chose to. They decided that the product just wasn’t good enough yet, and they wanted t

21 Jul 2026

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Previously, these AI hacking stories were about breaches in test environments, where any question of AI breaching security was purely theore…

applicationsethan-mollick--x

Previously, these AI hacking stories were about breaches in test environments, where any question of AI breaching security was purely theoretical. This is something else. https://openai.com/index/hugg

21 Jul 2026

Livestream Alert: Open World Models in Production: @ltx_io and ComfyUI Founders Live A special live conversation with @yoland_yan ( CEO, Com…

Livestream Alert: Open World Models in Production: @ltx_io and ComfyUI Founders Live A special live conversation with @yoland_yan ( CEO, ComfyUI ) & comfyanonymous ( Founder, ComfyUI ) and @ZeevFarbma

applicationscomfyui--x

20 Jul 2026

Our first DevRel office hours kicks off tomorrow. Come chat with our Head of AI Education @Prof_OZ about anything and everything AI.

applicationsfireworks-ai--x

Our first DevRel office hours kicks off tomorrow. Come chat with our Head of AI Education @Prof_OZ about anything and everything AI. Want to chat live with me about fine-tuning, Kimi K3, or really any

20 Jul 2026

Adapting Generalist Vehicle Models for High-Speed MPC Across Terrains

arXiv:2607.13319v1 Announce Type: cross Abstract: High-speed off-road autonomy requires precise closed-loop control for a target vehicle while remaining robust across changing terrains. Recent forward

AI-Augmented Adaptive Digital Twin Modeling for Brain Tumor Evolution Prediction and Treatment Scheduling

arXiv:2607.13877v1 Announce Type: new Abstract: Brain tumor progression exhibits spatially heterogeneous growth, patient-specific treatment response, and complex interactions with surrounding anatomy,

Attention-Free and Lightweight Token Reduction for Efficient Vision-Language Models

arXiv:2607.13500v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have achieved strong performance in multimodal understanding, yet remain challenging to deploy on resource-constrained edg

Efficient LiDAR Reflectance Compression via Scanning Serialization

arXiv:2505.09433v3 Announce Type: replace Abstract: Reflectance attributes in LiDAR point clouds provide essential information for downstream tasks but remain underexplored in neural compression metho

GHR-VLM: Making Zero-Shot Transit Video Analytics Realizable with Grounded Hybrid Reasoning

arXiv:2607.13569v1 Announce Type: cross Abstract: Transit video understanding can provide valuable fine-grained data that conventional passenger counters and fare systems cannot capture. However, supe

Improving Wind and Solar Power Prediction with Efficient Wrapper-based Feature Selection: An Empirical Study

arXiv:2607.14024v1 Announce Type: cross Abstract: With rising global energy demand and growing awareness of climate change and its impacts, the share of renewable energies in the global energy mix con

Learning Physics-Guided Residual Dynamics for Deformable Object Simulation

arXiv:2607.13451v1 Announce Type: cross Abstract: Simulating deformable objects is essential for a wide range of robotic manipulation applications, yet accurately predicting their dynamics remains cha

Learning Speaker Identity Beyond Language and Modality Constraints: Insights from the POLY-SIM 2026 Challenge

arXiv:2607.13669v1 Announce Type: new Abstract: Multimodal speaker identification systems typically assume the availability of complete and homogeneous audio-visual modalities during both training and

LPM: Industrial-Scale Generative Video Restoration

arXiv:2607.13460v1 Announce Type: new Abstract: We present the Large Processing Model (LPM), a diffusion-based generative framework for photorealistic video restoration under complex, in-the-wild degr

M2P-AD: Memory-to-Prototype Learning with Boundary-aware Score Refinement for 3D Anomaly Detection

arXiv:2607.13499v1 Announce Type: new Abstract: 3D anomaly detection has recently emerged as an important research topic in computer vision. Although existing methods have achieved high performance, e

MetaPerch: Learning from metadata for bioacoustics foundation models

arXiv:2607.14072v1 Announce Type: new Abstract: Bioacoustic foundation models rely on large-scale citizen science platforms like Xeno-Canto for geographically and ecologically diverse data. Recent wor

Microstructure-Conditioned Surrogate Models for Graded Multiscale Optimization of Mycelium Composites

arXiv:2607.13688v1 Announce Type: new Abstract: Emerging sustainable materials increasingly rely on engineered hierarchy and microstructure to achieve control of their properties and mechanical behavi

Multi-Expert Routing for Multi-Domain Low-Resource OCR: A Manchu Case Study

arXiv:2607.14041v1 Announce Type: cross Abstract: Historical Manchu OCR must accommodate various visually distinct writing styles, including regular script, running script, and the semi-cursive chance

Multi-view Hand Reconstruction with a Point-Embedded Transformer

arXiv:2408.10581v3 Announce Type: replace Abstract: This work introduces a novel and generalizable multi-view Hand Mesh Reconstruction (HMR) model, named POEM, designed for practical use in real-world

NodeImport: Imbalanced Node Classification with Node Importance Assessment

arXiv:2607.13837v1 Announce Type: cross Abstract: In real-world applications, node classification on graphs often faces the challenge of class imbalance, where majority classes dominate training, resu

Semantic Anchoring for Robotic Action Representations

arXiv:2607.13597v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models inherit rich semantic representations from pretrained Vision-Language Models, yet fine-tuning on limited robot dem

STKAN: Kolmogorov-Arnold Networks for Spatio-Temporal Forecasting

arXiv:2607.13108v1 Announce Type: cross Abstract: Real-world traffic data exhibit heterogeneous spatial correlations and nonlinear temporal dynamics, posing substantial challenges for accurate spatio-

Towards a Modular Bin-picking Framework for Handling Object Pose Uncertainties

arXiv:2607.13698v1 Announce Type: cross Abstract: In recent years, there has been growing interest in robust robotic systems for precise bin-picking applications. To achieve reliable performance, such

Towards end-to-end optimization in multimaterial 3D printing

arXiv:2607.13174v1 Announce Type: cross Abstract: Multimaterial 3D printing enables the fabrication of functionally graded components, but optimizing their spatial material distribution alongside stru

VAMP-MR: Vector-Accelerated Motion Planning and Execution for Multi-Robot-Arms

arXiv:2607.13478v1 Announce Type: new Abstract: Multi-robot-arm motion planning is a key challenge in deploying multiple manipulators for industrial tasks such as manufacturing. Existing search-based

Verifier-Guided Twelve-Tone Composition: A Generate-Verify-Repair Harness for Symbolic Music Generation

arXiv:2607.11334v2 Announce Type: replace Abstract: Large language models can produce superficially legal twelve-tone scores that collapse into degenerate textures. We introduce a neuro-symbolic harne

Worlds in One Demo: A Synthetic Data Engine for Learning Open-World Mobile Manipulation

arXiv:2607.13154v1 Announce Type: new Abstract: Learning open-world mobile manipulation policies requires vast data to achieve spatial generalization, long-horizon robustness, and scene generalization

A Bearing-Strength Method for Motion Estimation of Unknown Energy Emitters

arXiv:2607.12515v1 Announce Type: new Abstract: This paper studies motion estimation of moving energy emitters using passive sensors. The emitters may be light, acoustic, or radio sources. While the b

A Longitudinal Analysis of Public Discourse on AI Ethics in Education Using Twitter Data

arXiv:2607.12295v1 Announce Type: cross Abstract: The rapid integration of artificial intelligence (AI) and generative AI (GenAI) into education presents significant opportunities to enhance teaching

AdaPCLA: Adaptive Prior-Calibrated Logit Adjustment for Long-Tailed Longitudinal EHR Generation

arXiv:2607.12645v1 Announce Type: new Abstract: Generative modeling of longitudinal Electronic Health Records is increasingly important for privacy-preserving research, yet standard autoregressive mod

An Empirical Analysis of Continual Learning for Heterogeneous Medical Visual Question Answering

arXiv:2607.12048v1 Announce Type: cross Abstract: Deploying medical visual question answering (MedVQA) systems in real-world clinical settings requires models that adapt to new clinical tasks without

Answering Without Referring: How AI Search Rewrites the Web's Economic Bargain

arXiv:2607.07652v1 Announce Type: cross Abstract: Search engines have long allocated attention on the web by routing users from queries to websites. AI search changes this arrangement because informat

Atomic Units of X: The Compression Layer of Intelligence

arXiv:2607.12634v1 Announce Type: new Abstract: This paper proposes a theoretical framework for understanding intelligence as a process of atomic compression and compositional reuse. We argue that cog

Built Technologies builds an AI-powered document intelligence solution on AWS to power agents across real estate finance

Built partnered with the AWS Generative AI Innovation Center (GenAIIC), AWS Partner AND Digital, and AWS account teams to create a scalable, AI-powered document processing engine that can classify, sp

applicationsaws-ml-blog

calling it now FDE -> ODE -> PDE the existence of Forward Deployed Engineering and now Ordinary Deployed Engineering implies that the next p…

calling it now FDE -> ODE -> PDE the existence of Forward Deployed Engineering and now Ordinary Deployed Engineering implies that the next pokemon evolution is Partial Deployed Engineering Anthropic,

applicationsswyx--x

Causal Supervision of Attention for Affective Behaviour Analysis

arXiv:2607.12091v1 Announce Type: new Abstract: Affective Behaviour Analysis aims to enable machines to infer human affective states from behavioural signals, particularly facial expressions, in real-

Color Pass-Through via Camera-Display Coupling

arXiv:2607.12746v1 Announce Type: new Abstract: When a real-world scene is captured by a smartphone camera and viewed on its screen, the displayed image often differs noticeably from the original scen

Contrastive-Augmented Flow Matching for Style-Content Disentanglement

arXiv:2607.12404v1 Announce Type: new Abstract: Learning representations that separate content and style is crucial for controllable generation and compositional generalization. However, diffusion and

Cost-Governed RAG: Unified Per-Tenant Cost Attribution Across Retrieval and Generation in Multi-Tenant LLM Systems

arXiv:2607.12188v1 Announce Type: new Abstract: Enterprise Retrieval-Augmented Generation (RAG) deployments face a critical governance gap: while LLM generation cost is metered per token, the retrieva

Creatio expands beyond its no-code roots with conversational development tool and AI studio

Creatio Inc. today introduced what it calls a major update to its customer relationship management and workflow platform that enables business users and information technology teams to build, deploy a

applicationssiliconangle

DA-Nav: Direction-Aware City-Scale Vision-Language Navigation

arXiv:2607.11638v2 Announce Type: replace Abstract: City-scale outdoor navigation is currently hindered by the heavy reliance on dense maps or costly navigation supervision. In this work, we introduce

Data-Native AI Agents: Why Agents Must Move to Your Data

Enterprise AI agents lose effectiveness when they must access data outside of protected, governed systems. The article argues that truly reliable agents need to be *data‑native*—run directly inside th

applicationsdatabricks

DermDepth: Toward Monocular Metric Scale 3D Reconstruction Models for Dermatology

arXiv:2607.13010v1 Announce Type: new Abstract: Dermatological practice routinely involves measuring and tracking lesion size, morphology and texture, as critical components of wound or skin cancer sc

Enabling Energy-Efficient Simultaneous Multi-Task Reinforcement Learning through Spiking Neural Networks with Active Dendrites for Bio-inspired Generalist Agents

arXiv:2412.04847v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has demonstrated remarkable capabilities in training agents to solve complex tasks autonomously, such as mobile ro

Evaluating Reliability in Machine Learning Models for Early Chronic Kidney Disease Prediction: A Systematic Review of Data Leakage and Predictor Stability

arXiv:2607.11963v1 Announce Type: cross Abstract: The early detection of Chronic Kidney Disease using machine learning has attracted significant interest in healthcare-related computer science. Despit

FAIR GraphRAG: A Retrieval-Augmented Generation Approach for Semantic Data Analysis

arXiv:2607.11464v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) addresses the limitations of Large Language Models (LLMs) when providing responses to domain-specific questions.

“I asked a few AI researchers whether they could name any other real-world software that scales so poorly. None of them could think of any. …

applicationsgary-marcus--x

“I asked a few AI researchers whether they could name any other real-world software that scales so poorly. None of them could think of any. Even outside the world of software, it’s hard to find a comp

Inclusive Federated Learning Through Compliance-Weighted Noise Allocation in Healthcare AI

arXiv:2505.22108v4 Announce Type: replace-cross Abstract: Background: Federated learning (FL) enables collaborative training of clinical AI models without centralizing patient data, but adoption is li

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation

arXiv:2505.15284v2 Announce Type: replace-cross Abstract: Out-of-Distribution (OoD) detection is vital for the reliability of deep neural networks, the key of which lies in effectively characterizing