applications

Neural operator discovery from heterogeneous trajectories

arXiv:2607.23337v1 Announce Type: new Abstract: Neural operators provide data-driven mappings for modeling dynamical systems. Extending them to families of systems typically requires explicit conditio

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OpenAI and Anthropic release statements in support of the 'Pacing the Frontier' initiative; Anthropic says Dario Amodei and several co-founders have signed it (Anhata Rooprai/Reuters)

DGX agent

Anhata Rooprai / Reuters: OpenAI and Anthropic release statements in support of the “Pacing the Frontier” initiative; Anthropic says Dario Amodei and several co-founders have signed it — More than 1,1

applicationstechmeme

28 Jul 2026

Ordering-based Causal Discovery via Generalized Score Matching

arXiv:2601.16249v3 Announce Type: replace-cross Abstract: Learning DAG structures from purely observational data remains a long-standing challenge across scientific domains. An emerging line of resear

ORGAN: Object-Centric Representation Learning using Cycle Consistent Generative Adversarial Networks

arXiv:2603.02063v2 Announce Type: replace Abstract: Although data generation is often straightforward, extracting information from data is more difficult. Object-centric representation learning can ex

Quantum Safe-Set Bayesian Optimization for Quality Improvement in Fuselage Assembly

arXiv:2511.22090v2 Announce Type: replace Abstract: Recent efforts in smart manufacturing have enhanced aerospace fuselage assembly processes, particularly by innovating shape adjustment techniques to

Real-time Reconstruction of Human Visual Perception from fMRI

arXiv:2607.22753v1 Announce Type: cross Abstract: Real-time closed-loop neurofeedback based on functional magnetic resonance imaging (fMRI) has led to important scientific and clinical advances. Howev

Scoping Review of AI, Metrology, and ESG in the Semiconductor Sector: Implications for Safe and Sustainable by Design (SSbD)

arXiv:2607.23082v1 Announce Type: cross Abstract: The semiconductor sector faces a dual transition: scaling manufacturing execution through Artificial Intelligence (AI) while satisfying stringent sust

Semantic Semi-Incremental Data-Association-Free Object SLAM

arXiv:2607.23384v1 Announce Type: cross Abstract: Data association between landmark measurements and landmark variables has long been a central challenge in SLAM, as estimation accuracy depends critic

SeT-Diff: Towards Semantic Foundation Models for HPC Telemetry and Time-Series

arXiv:2607.22548v1 Announce Type: new Abstract: Data centers and their compute nodes require accurate and flexible digital twins capable of modeling the complex interplay of workloads, environmental p

The Illusion of Secure LLM Code: Closing the Security Gap via Iterative Reprompting

arXiv:2607.23710v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into software development workflows, yet their ability to autonomously generate secure authen

The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing

arXiv:2607.24396v1 Announce Type: cross Abstract: In deep learning, efficiency gets more and more important to compensate for the ongoing growth in model sizes and applications. Neuromorphic hardware

There is definitely real jaggedness both among fields (writing is an area where models improve slowly if at all) and within them, but the ma…

applicationsethan-mollick--x

There is definitely real jaggedness both among fields (writing is an area where models improve slowly if at all) and within them, but the magic of LLMs is that they are so unreasonably effective acros

There's been a talk about how LLMs are only advancing in verifiable areas like math or coding, but that isn't what the data suggests. As mod…

applicationsethan-mollick--x

There's been a talk about how LLMs are only advancing in verifiable areas like math or coding, but that isn't what the data suggests. As models have gotten better at that, they are also better at solv

TRACE: Business Rule-Grounded Reasoning Curriculum for Knowledge-Preserving Parametric Tool Retrieval in Enterprise LLMs

arXiv:2607.22639v1 Announce Type: new Abstract: Parametric retrieval enables LLMs to retrieve tools implicitly by assigning each API a unique virtual token and training the model to generate it via co

Traceable LLM Reasoning for Fake-Order Fraud Detection

arXiv:2607.23075v1 Announce Type: cross Abstract: Detecting fake-order fraud at scale remains a critical challenge for large online-to-offline (O2O) service platforms, as existing approaches often rel

VEMamba: Efficient Isotropic Reconstruction of Volume Electron Microscopy with Axial-Lateral Consistent Mamba

arXiv:2603.00887v2 Announce Type: replace Abstract: Volume Electron Microscopy (VEM) is crucial for 3D tissue imaging but often produces anisotropic data with poor axial resolution, hindering visualiz

Visible to the Court: How AI Is (and Isn't) Litigated in U.S. Federal Court Opinions

arXiv:2607.23888v1 Announce Type: cross Abstract: In the United States, artificial intelligence (AI) is rapidly deployed amid limited federal regulation. With courts become a recurring forum in which

Visual Information Extraction from Documents via Classification-Guided Large Vision-Language Models

arXiv:2607.22723v1 Announce Type: new Abstract: Visual information extraction (VIE) from visually rich documents remains challenging due to high layout variability and real-world impairments. Existing

Where Quality Breaks in Compressed Short-Text Generation: Staged Bottleneck Localization

arXiv:2607.24176v1 Announce Type: new Abstract: Compressed short-text generators can fail in two different places: the codec may discard information before generation starts, or the latent generator m

A Monolithic Hand with Asymmetric Origami Bending and Dual-chamber Actuators

arXiv:2607.22320v1 Announce Type: new Abstract: The passive adaptability inherent in soft robotic hands affords them advantages in applications that require safe and compliant interaction. However, ex

A Robust Pipeline for Differentially Private Federated Learning on Imbalanced Clinical Data using SMOTETomek and FedProx

arXiv:2508.10017v2 Announce Type: replace-cross Abstract: Federated Learning (FL) presents a groundbreaking approach for collaborative health research, allowing model training on decentralized data wh

A Unified Framework for Automated Assembly Sequence and Production Line Planning using Graph-based Optimization

arXiv:2512.13219v2 Announce Type: replace Abstract: This paper presents PyCAALP (Python-based Computer-Aided Assembly Line Planning), a framework for automated Assembly Sequence Planning (ASP) and Pro

Biomedical Machine Translation for Low-Resource Arabic-Script Languages via Cross-Lingual Transfer and LoRA Adapter Merging

arXiv:2607.22300v1 Announce Type: new Abstract: We present a systematic study of healthcare-domain cross-lingual transfer to address the scarcity of biomedical NMT resources for Arabic-script language

CARNet Cycle-Conditioned Core Aggregation and Redistribution for Multivariate Time Series Forecasting

arXiv:2607.21681v1 Announce Type: new Abstract: Accurately modeling cross-variate dependencies remains a key challenge in multivariate time series forecasting, particularly in the presence of strong p

ChatGPT appears to block direct requests to copy an author's style, instead offering to capture the overall 'feeling', amid its legal battles with book authors (Kyle Orland/Ars Technica)

Kyle Orland / Ars Technica: ChatGPT appears to block direct requests to copy an author's style, instead offering to capture the overall “feeling”, amid its legal battles with book authors — OpenAI's C

applicationstechmeme

Closing the Loop: Training-Free Revisit Consistency for Autoregressive Generative Rendering

arXiv:2607.21848v1 Announce Type: new Abstract: Recent conditional video generation models have shown promising potentials to transform 3D engine renderings, such as depth maps and untextured geometry

Efficient Recommendations via Graph Coarsening and Label Propagation

arXiv:2607.22287v1 Announce Type: new Abstract: Graph-based recommendations are widely adopted in real-world industrial applications. However, graphs in these systems often reach a massive scale, posi

Farmland Extent and Visible Boundary Mapping from 1 m NAIP Imagery Using Residual U-Net and Text-Prompted SAM 3 Refinement

arXiv:2607.21881v1 Announce Type: new Abstract: Agricultural field maps are often proprietary, incomplete, or outdated, yet they provide the spatial framework for crop monitoring, production accountin

Geometric 2D Scene Graph Generation

arXiv:2607.22325v1 Announce Type: new Abstract: In production processes for consumer products, assembly instructions are essential not only for planning but also for executing the production process.

gp2Scale: A Class of Compactly Supported Non-Stationary Kernels and Distributed Computing for Exact Gaussian Processes on 10 Million Data Points

arXiv:2512.06143v2 Announce Type: replace Abstract: Despite a large corpus of recent work on scaling up Gaussian processes, a stubborn trade-off between computational speed, prediction and uncertainty

GPT-Live in ChatGPT Voice is now available to Edu, Business, and Enterprise plans globally.

GPT-Live in ChatGPT Voice is now available to Edu, Business, and Enterprise plans globally. Introducing GPT-Live, a new generation of voice models for natural human-AI interaction. Rolling out in Chat

applicationsopenai--x

Graph-Based Correlation Matrix Generation: A Convex Optimization Approach

arXiv:2607.22436v1 Announce Type: cross Abstract: This work addresses the generation of theoretical correlation matrices with prescribed sparsity patterns associated to graph structures. We propose a

grapheme-kit: Grapheme-Level Metrics and Text Processing for Multilingual NLP

arXiv:2607.22456v1 Announce Type: new Abstract: Existing lexical distance, similarity, and evaluation metrics operate on Unicode code points, which can misrepresent errors in writing systems where a s

HD3C: Efficient Medical Data Classification for Edge Devices

arXiv:2509.14617v4 Announce Type: replace Abstract: Efficient medical data classification is essential for modern disease screening, particularly in resource-constrained environments where power budge

Impedance Control of Ship-Borne Manipulators via Optimization-based Task-Space Inverse Dynamics

arXiv:2607.22030v1 Announce Type: new Abstract: Ship-borne manipulators operating in maritime environments are subject to stochastic wave-induced base motions that introduce kinematic disturbances and

Integrated Order Dispatching and Routing for Last-Mile Pickup via Deep Reinforcement Learning

arXiv:2607.22356v1 Announce Type: new Abstract: In recent years, the growing complexity of last-mile pickup operations has increased the need for fast and accurate decision-making on logistics platfor

Kimi K3 is live on @FireworksAI_HQ As per usual not only are we fast AF but we take quality as a P0 and never sacrifice quality for anything…

applicationsfireworks-ai--x

Kimi K3 is live on @FireworksAI_HQ As per usual not only are we fast AF but we take quality as a P0 and never sacrifice quality for anything (only OSS provider to top Moonshot's evals across the board

Last week, we made ChatGPT Work available to enterprises. It's an awesome product. So for ChatGPT Enterprise customers, enroll by August 21,…

Last week, we made ChatGPT Work available to enterprises. It's an awesome product. So for ChatGPT Enterprise customers, enroll by August 21, and each teammate who tries Work for the first time within

applicationsopenai--x

Meta-Learning Approaches for Speaker-Dependent Voice Fatigue Models

arXiv:2505.23378v3 Announce Type: replace Abstract: Speaker-dependent modelling can substantially improve performance in speech-based health monitoring applications. While mixed-effect models are comm

Prompt as a Data Type: In-Database LLM Prompt Management and Rewriting

arXiv:2607.21756v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in database-backed applications to classify tuples, filter records using semantic predicates, extra

Simulation-Based Empirical Bayes

arXiv:2607.21843v1 Announce Type: cross Abstract: Empirical Bayes (EB) performs simultaneous inference across many related latent variables. Classical EB assumes that the likelihood p(x | z) is tracta

SM4RT: Learning Structured Motion Geometry for 4D Reconstruction

arXiv:2607.22534v1 Announce Type: new Abstract: Geometry Foundation Models (GFMs) have substantially advanced monocular 3D reconstruction, yet extending this capability to 4D dynamic understanding rem

Start owning your own intelligence today with Kimi K3 on Fireworks. Serve it, fine-tune it, and put it into production. What are you waiting…

applicationsfireworks-ai--x

**Summary:** Kimi K3 is a publicly available 3‑trillion‑parameter language model now live on Fireworks, offering 1 million-token context windows with native vision and reasoning that rivals top closed

Teachy Mini: Development and Preliminary Evaluation of a Knowledge-Based Generative Social Robot for Higher Education

arXiv:2607.22345v1 Announce Type: new Abstract: Generative social robots (GSRs) powered by large language models offer new possibilities for personalized tutoring in higher education, but also introdu

Token-Operations-Oriented Inference Optimization Techniques for Large Models

arXiv:2606.20295v2 Announce Type: replace-cross Abstract: Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large mode

How AI companies are targeting the education market, including making free or cut-price tailored learning tools in partnership with schools and edtech startups (Jamie John/Financial Times)

Jamie John / Financial Times: How AI companies are targeting the education market, including making free or cut-price tailored learning tools in partnership with schools and edtech startups — Anthropi

applicationstechmeme

26 Jul 2026

A Diffusion-Model Subpopulation Digital Twin for Mobile Health Deployment: A Case Study on the HeartSteps Intervention

arXiv:2607.21403v1 Announce Type: new Abstract: Mobile-health interventions increasingly use online learning and decision making algorithms to personalize when to nudge users toward healthier behavior

24 Jul 2026

A Graph Neural Network approach to zero-shot Digital Twins

arXiv:2607.20535v1 Announce Type: cross Abstract: Traditional Predictive Digital Twins often remain geometrically rigid, requiring extensive retraining or fine-tuning whenever the underlying physical