applications

A Novel Computer Vision Approach for Assessing Fish Responses to Intrusive Objects in Aquaculture

arXiv:2605.30399v1 Announce Type: cross Abstract: The aquaculture industry needs to address several challenges to secure sustainable seafood production that can serve an increasing global demand. One

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Advances and Challenges in Meta-Learning: A Technical Review

DGX agent

arXiv:2307.04722v2 Announce Type: replace Abstract: Meta-learning empowers learning systems with the ability to acquire knowledge from multiple tasks, enabling faster adaptation and generalization to

applicationsarxiv-cs-lg

1 Jun 2026

AdvScene: Rethinking Adversarial Patch Evaluation Through Scene Robustness

arXiv:2605.30578v1 Announce Type: cross Abstract: Adversarial patches are physical patterns attached to real objects to mislead AI vision systems. Their real-world risk is not determined by a single s

Algorithmic Recourse of In-Context Learning for Tabular Data

arXiv:2605.31272v1 Announce Type: new Abstract: As predictive models are increasingly deployed in high-stakes settings such as credit approval, there is a growing need for post-hoc methods that provid

Allegedly trashing Airbnbs to test robots puts startup in legal trouble

The Bot Company, a 2 billion San Francisco startup founded by Tesla and Cruise alumni, rented residential properties through Airbnb under false pretenses to conduct prototype testing on household robo

applicationsars-technica

An Efficient and Scalable Graph Condensation with Structure-Preserving

arXiv:2605.31016v1 Announce Type: new Abstract: Graph condensation (GC) is pivotal for enabling Graph Neural Networks (GNNs) deployment in resource-constrained scenarios by compressing large-scale gra

Astra: a generalizable report generation foundation model for 3D computed tomography

arXiv:2605.31437v1 Announce Type: new Abstract: CT interpretation requires radiologists to review hundreds of volumetric slices per examination, making reporting time-consuming and highly expertise-de

Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors

arXiv:2605.05520v2 Announce Type: replace Abstract: Commercial Microwave Links (CMLs) offer dense spatial coverage for rainfall sensing but produce path-integrated measurements that make accurate grou

Benchmarking Single-Step Inpainting Methods for Multi-Object 3D Gaussian Splatting Scenes

arXiv:2605.30987v1 Announce Type: new Abstract: The tasks of object removal and inpainting 3D Gaussian Splatting (3DGS) scenes face challenges such as 3D consistency across camera views. In comparing

Beyond Memorization: Assessing Semantic Generalization in Large Language Models Using Phrasal Constructions

arXiv:2501.04661v3 Announce Type: replace-cross Abstract: The web-scale of pretraining data has created an important evaluation challenge: to disentangle linguistic competence on cases well-represente

Bundesrecht: An Open Library and Corpus for German Statutory Reference Processing

arXiv:2605.31338v1 Announce Type: new Abstract: Statutory references are central to legal language understanding, but are difficult to process automatically, as they appear in compact and variable sur

applicationsarxiv-cs-cl

Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement

arXiv:2605.30981v1 Announce Type: new Abstract: Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibitin

applicationsarxiv-cs-cl

Cross-Modal Clinical Knowledge Integration for Mammography Report Generation

arXiv:2605.31093v1 Announce Type: new Abstract: Breast cancer is a major global health concern, and mammography screening plays a central role in early detection. The large volume of screening examina

D^3: Dynamic Directional Graph-Constrained Data Scheduling for LLM Training

arXiv:2605.31164v1 Announce Type: cross Abstract: Training data plays a central role in large language models (LLMs) optimization, motivating extensive research on data scheduling strategies. Most exi

Diffusion Models Preferentially Memorize Prototypical Examples or: Why Does My Diffusion Model Love Slop?

arXiv:2605.30642v1 Announce Type: new Abstract: Generative models have a persistent limitation: their tendency to memorize training data can create legal liabilities and erode creative diversity. Unde

DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers

arXiv:2605.30456v1 Announce Type: new Abstract: Many learning tasks in science and engineering are characterized by sparse datasets, which limits the effectiveness of purely data-driven approaches. At

Do Large Language Models Encode Institutional Experience? Evidence from Cross-Linguistic Moral Reasoning Under Ambiguity

arXiv:2605.30934v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit systematic differences in moral reasoning across languages, yet the source of this variation remains unclear. We

Enhancing Computer Vision Model Generalization in Warehouse Facilities: A Case Study on Anomaly Detection in Vertical Material Handling Systems

arXiv:2605.31487v1 Announce Type: new Abstract: Deploying computer vision models in Warehouse Facilities traditionally requires extensive resources for camera mounting, image collection, annotation, t

Feature-Aware (Hyper)graph Generation via Next-Scale Prediction

arXiv:2506.01467v3 Announce Type: replace Abstract: Graph generative models perform well on small structured data but struggle to scale to large, complex structures. Hierarchical approaches improve sc

FlexRank: Nested Low-Rank Knowledge Decomposition for Adaptive Model Deployment

arXiv:2602.02680v2 Announce Type: replace Abstract: The growing scale of deep neural networks, encompassing large language models (LLMs) and vision transformers (ViTs), has made training from scratch

For those who wants stats, rather than anecdotes https://x.com/emollick/status/1983217724714066310?s=20

applicationsethan-mollick--x

For those who wants stats, rather than anecdotes https://x.com/emollick/status/1983217724714066310?s=20 👀New data on the corporate ROI from generative AI from a large-scale tracking survey by my colle

Geometry-based Schrodinger Bridges for Trustworthy Multimodal Fusion

arXiv:2605.31193v1 Announce Type: new Abstract: Real-world multimodal systems must be robust against low-quality data, such as sensor noise, incomplete multimodal data and conflicting inputs. However,

GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration

arXiv:2605.31039v1 Announce Type: new Abstract: Real-world image restoration (IR) is bottlenecked by the scarcity of high-quality paired training data. Synthetic datasets are abundant but often fail t

Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring

arXiv:2605.30834v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models enable robots to follow natural language instructions and generalize across diverse tasks, but they remain vulnera

HPE reports Q2 revenue up 40% YoY to 10.7B, vs. 9.74B est., Server revenue up 33%, forecasts revenue for FY26 and FY27 above est.; HPE jumps 30%+ after hours (Brody Ford/Bloomberg)

Brody Ford / Bloomberg: HPE reports Q2 revenue up 40% YoY to 10.7B, vs. 9.74B est., Server revenue up 33%, forecasts revenue for FY26 and FY27 above est.; HPE jumps 30%+ after hours — Hewlett Packard

applicationstechmeme

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

arXiv:2501.12500v3 Announce Type: replace Abstract: Understanding climate dynamics requires going beyond correlations in observational data to uncover the underlying causal process. Latent drivers suc

Learning to Solve and Optimize by Evolving Code

arXiv:2605.31049v1 Announce Type: cross Abstract: Combinatorial and optimization problems are fundamental to many industrial AI applications. Solving large-scale real-world instances of such problems

MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding

arXiv:2605.30794v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated significant achievements in general visual question answering (VQA) tasks. However, they re

Neither Replacement nor Panacea: Comparing LLM-Based Conversational and Graphical Decision Support in Industrial Tasks

arXiv:2605.31287v1 Announce Type: cross Abstract: Managers in manufacturing settings rely on digital interfaces to interpret operational data for decision-making, but growing data volume and complexit

Non-destructive Identification of Oyster Species is possible from Hyperspectral Images with Machine Learning

arXiv:2605.30811v1 Announce Type: new Abstract: Differentiating between oyster species is important for developing new commercial oyster species suited to production systems and is critical for tracea

Notes-to-Self: Scratchpad Augmented VLAs for Memory Dependent Manipulation Tasks

arXiv:2602.21013v2 Announce Type: replace Abstract: Many dexterous manipulation tasks are non-markovian in nature, yet little attention has been paid to this fact in the recent upsurge of the vision-l

applicationsarxiv-cs-ro

NumLeak: Public Numeric Benchmarks as Latent Labels in Foundation Models

arXiv:2605.30393v1 Announce Type: cross Abstract: Public numeric benchmarks appear in pretraining, so an evaluation that conditions on a date may be measuring memorized recall rather than out-of-sampl

OLG++: A Semantic Extension of Obligation Logic Graph

arXiv:2507.05488v2 Announce Type: replace Abstract: We present OLG++, a semantic extension of the Obligation Logic Graph (OLG) for modeling regulatory and legal rules in municipal and interjurisdictio

OpenAI frontier models and Codex are now available on AWS

OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new path to build with OpenAI through the AWS environments, controls, and procurement workflows they already u

applicationsopenai

OrcaRouter: A Production-Oriented LLM Router with Hybrid Offline-Online Learning

arXiv:2605.30736v1 Announce Type: cross Abstract: The rapid development of large language models, each with distinct capabilities and inference costs, raises a practical deployment question: given an

Performance and Complexity Trade-off Optimization of Speech Models During Training

arXiv:2601.13704v3 Announce Type: replace-cross Abstract: In speech machine learning, neural network models are typically designed by choosing an architecture with fixed layer sizes and structure. The

Positional versus Symbolic Attention Heads: Learning Dynamics, RoPE Geometry, and Length Generalization

arXiv:2605.31558v1 Announce Type: cross Abstract: Transformer-based language models are widespread in today's society. As such, understanding the mechanisms by which they solve structured tasks and pr

Prior Availability in Industrial Visual Sim-to-Real: A Review of CAD-Guided and CAD-Unavailable Regimes

arXiv:2605.30581v1 Announce Type: cross Abstract: Industrial visual sim-to-real is often described as transferring from synthetic images to real images, but industrial deployment usually involves a br

PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection

arXiv:2502.12119v4 Announce Type: replace-cross Abstract: Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications

Production AI systems place very different demands on infrastructure once workloads scale. How? Join us at #MSBuild to find out. Register he…

applicationsfireworks-ai--x

Production AI systems require fundamentally different infrastructure approaches as workloads scale, with demands that differ significantly from development or testing environments. Fireworks AI discus

RayDer: Scalable Self-Supervised Novel View Synthesis from Real-World Video

arXiv:2605.31535v1 Announce Type: cross Abstract: Self-supervised novel view synthesis (NVS) remains challenging to scale, despite the abundance of video data, largely due to the brittleness of traini

ReGuLaR: Relation-Grounded Latent Reasoning for Large Vision-Language Models

arXiv:2605.30587v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has significantly improved the reasoning ability of large vision-language models (LVLMs) by verbalizing intermediate re

Reliable Multilingual Orthopedic Decision Support from Clinical Narratives: Language-Aware Adaptation and Verification-Guided Deferral

arXiv:2605.31512v1 Announce Type: new Abstract: Multilingual orthopedic decision support remains challenging in low-resource healthcare settings, where clinical narratives contain specialized terminol

applicationsarxiv-cs-cl

SAM for Robust Mitochondria Instance Segmentation in Fluorescence Microscopy

arXiv:2605.31284v1 Announce Type: cross Abstract: The morphological analysis of mitochondria in fluorescence microscopy (FM) is crucial for understanding cellular health, energy production, and metabo

Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction

arXiv:2605.30593v1 Announce Type: cross Abstract: Engine Health Management (EHM) depends on reliable forecasting of Remaining Useful Life (RUL) and on tracking thermal indicators such as turbine gas t

Shaft-integrated Force Sensing with Transformer-based Dynamics Compensation for Telesurgery

arXiv:2605.31434v1 Announce Type: new Abstract: Robot-Assisted Minimally Invasive Surgery (RAMIS) enhances surgeon dexterity, with newer platforms leveraging haptic feedback to further improve perform

applicationsarxiv-cs-ro

SignScene: Visual Sign Grounding for Mapless Navigation

arXiv:2602.12686v2 Announce Type: replace Abstract: Navigational signs enable humans to navigate unfamiliar environments without maps. This work studies how robots can similarly exploit signs for mapl

applicationsarxiv-cs-ro

SKETCH: Semantic Key-Point Conditioning for Long-Horizon Vessel Trajectory Prediction

arXiv:2601.18537v3 Announce Type: replace-cross Abstract: Accurate long-horizon vessel trajectory prediction remains challenging due to compounded uncertainty from complex navigation behaviors and env