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Very interesting to see @JeffDean's pitch deck. Just look at those open science and engineering problems. Lots to advance there with automat…

Very interesting to see @JeffDean's pitch deck. Just look at those open science and engineering problems. Lots to advance there with automated ML engineering. AI for science and engineering is just ge

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5 Aug 2026

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A Sequence-to-Sequence ConvLSTM Approach for Leaf Area Index Forecasting over the South-Central United States

DGX agent

arXiv:2608.00879v1 Announce Type: cross Abstract: Leaf Area Index (LAI) is a fundamental biophysical variable governing land-atmosphere interactions; however, LAI forecasting at high spatial resolutio

researcharxiv-cs-lg

4 Aug 2026

Local Ai

AirSplat: Alignment and Rating for Robust Feed-Forward 3D Gaussian Splatting

arXiv:2603.25129v2 Announce Type: replace Abstract: While 3D Vision Foundation Models (3DVFMs) have demonstrated remarkable zero-shot capabilities in visual geometry estimation, their direct applicati

local-aiarxiv-cs-cv

Artificial Intelligence for the Characterization of Particles and Fibers by Optical Microscopy

arXiv:2608.00361v1 Announce Type: new Abstract: Optical microscopy of particle and fiber dispersions involves interpreting subtle visual cues influenced by specimen morphology, chemical composition, m

Automatic Annotation of Ancient Greek Vowel Length

arXiv:2608.01935v1 Announce Type: new Abstract: Prior work in Ancient Greek NLP relies on corpora that do not disambiguate the phonemic vowel length of alpha, iota, and ypsilon, together known as the

Beyond Gene Reconstruction: Learning Cell Representations through Complementary Transcriptomic Views

arXiv:2608.00985v1 Announce Type: new Abstract: The rapid growth of single-cell transcriptomic data has enabled the development of foundation models pretrained primarily by reconstructing masked expre

tutorialsarxiv-cs-lg

Can AI Agents Simulate A/B Test Outcomes? A Validation Framework for Agentic Experimentation

arXiv:2608.02345v1 Announce Type: new Abstract: A/B testing remains the standard for rolling out new features in the technology industry. Each experiment, however, consumes real traffic, engineering e

agentsarxiv-cs-cl

Can You Trust the Confidence? ConfBench for Vision-Language Models on Document Extraction

arXiv:2608.01792v1 Announce Type: cross Abstract: Intelligent document processing (IDP) with vision-language models (VLMs) hinges on confidence scores trustworthy enough to route extractions between a

Causal Inference with Unstructured Treatments

arXiv:2608.00657v1 Announce Type: cross Abstract: Causal inference usually concerns a scalar treatment, yet in many problems the treatment is unstructured: a text, an image, or a sequence of clinical

tutorialsarxiv-cs-lg

CoLI: A Reproducible Platform for Continuum Robot Learning via Monolithic 3D Printing and Isomorphic Teleoperation

arXiv:2606.20389v2 Announce Type: replace Abstract: Continuum robots offer strong potential for manipulation tasks due to their high degrees of freedom, compliant structures, and operational safety. H

safetyarxiv-cs-ro

Constructing Parallel Multidimensional Chromatic Lexicons for Corpus-Assisted Analysis of Russian and English Texts

arXiv:2608.01752v1 Announce Type: new Abstract: This article addresses the relative scarcity of research tools for the corpus-assisted linguistic analysis of colour terms in literary texts. It describ

researcharxiv-cs-cl

Decoding Children's Gait Behavior

arXiv:2608.00371v1 Announce Type: new Abstract: We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We speci

Deep Learning-Based Estimation of Ground Reaction Forces in Parkinsonian Gait Using an Optimized Set of IMU Data

arXiv:2608.02408v1 Announce Type: new Abstract: Accurate gait analysis in Parkinson's disease (PD) typically relies on laboratory-based systems to capture biomechanical data, such as ground reaction f

Deep Learning for Cyber Threat Detection and Mitigation in Healthcare-IoT

arXiv:2608.00118v1 Announce Type: cross Abstract: Cybersecurity is a fundamental requirement for protecting wearable devices used in healthcare Internet of Things (H-IoT) systems. Security failures in

DiffPhysCam: Differentiable Physics-Based Camera Simulation for Inverse Rendering and Embodied AI

arXiv:2508.08831v2 Announce Type: replace-cross Abstract: Generating synthetic images that closely mimic those from real cameras is instrumental in training visual models and enabling end-to-end visuo

agentsarxiv-cs-cv

DiffuseAgent-MI: Distributionally-Grounded,Tool-Integrated Self-Evolving Agents for Faithful Visual Reasoning

arXiv:2608.00540v1 Announce Type: new Abstract: Tool-integrated vision-language agents have made remarkable progress on compositional and multi-step visual reasoning. Yet their outputs frequently exhi

safetyarxiv-cs-cv

DODA: A Database of Datasets for Aesthetics Research

arXiv:2608.00089v1 Announce Type: new Abstract: With rapid growth in the fields of empirical and computational aesthetics we have seen a vast increase in large image datasets annotated for aesthetics.

Local Ai

Dynamic Resolution Routing for Efficient Egocentric Grounding

arXiv:2608.01638v1 Announce Type: new Abstract: Egocentric visual grounding requires high-resolution inputs to localize small objects. However, scaling Multimodal Large Language Models to this domain

local-aiarxiv-cs-cv

Eigenvalues as a Metric for Memory Dynamics in Sequence Models

arXiv:2510.09379v2 Announce Type: replace Abstract: While softmax attention drives state-of-the-art performance in sequence modeling, its quadratic complexity motivates linear alternatives such as sta

Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data

arXiv:2608.00346v1 Announce Type: new Abstract: Data imbalance poses a major challenge in supervised classification, where the majority-class bias contributes to false negatives and overestimates clas

Evolutionary Curriculum Learning Improves Biological Sequence Modeling

arXiv:2608.00697v1 Announce Type: cross Abstract: Variational autoencoders (VAEs) trained on multiple sequence alignments (MSAs) have emerged as powerful generative models for biological sequences, wi

Fairness in Augmented Graph Learning: A Survey

arXiv:2504.21296v2 Announce Type: replace Abstract: Graph learning has evolved into Augmented Graph Learning (AGL) by integrating specialized machine learning (ML) techniques. Examples include federat

Feed-Forward Steering in Transformer Residual Dynamics

arXiv:2608.02071v1 Announce Type: new Abstract: Attention-only dynamical theories model Transformer residual directions as particles aggregating on a sphere. We extend this framework by incorporating

FRA-NBV: A Fast and Reflectivity-Aware Next-Best-View Strategy

arXiv:2608.01950v1 Announce Type: new Abstract: Autonomous 3D reconstruction with depth sensors is strongly affected by reflective surfaces, which cause missing or unreliable measurements and reduce t

agentsarxiv-cs-ro

Gaokerena: A Small Persian Medical Language Model Family

arXiv:2608.00932v1 Announce Type: new Abstract: The integration of artificial intelligence into medical question-answering systems has advanced rapidly; however, research remains predominantly focused

GeoCore-9B: Towards Geo-Aware Generative Foundation Models in Earth Observation

model-releasesarxiv-cs-cv

arXiv:2608.01896v1 Announce Type: new Abstract: Existing generative models for earth observation (EO) predominantly rely on fine-tuning natural image priors, which limits their scalability and introdu

Heterogeneous Multi-Agent Reinforcement Learning for Radio Resource Management under Coupled Finite-Horizon Constraints

arXiv:2608.01745v1 Announce Type: new Abstract: Maximizing throughput under proportional fairness in dense wireless networks requires jointly managing user association, scheduling, base station (BS) a

Hybrid Quantum CNN for Cross-Sensor Spaceborne Volcanic Thermal Activity Recognition Worldwide

arXiv:2608.00069v1 Announce Type: cross Abstract: As Earth Observation (EO) enters the Big Data era, the exponential volume of daily satellite imagery poses significant computational and storage chall

Interpretable machine learning for predicting splitting strength of asphalt concrete: insights from SHAP analysis

arXiv:2608.00956v1 Announce Type: new Abstract: This paper presents an interpretable machine-learning framework for predicting the splitting strength (ST) of asphalt concrete and supporting data-drive

Learning-Based Motion Planning for Dynamic Environments: From Foundational Algorithms to Emerging Paradigms

arXiv:2608.00625v1 Announce Type: new Abstract: Motion planning in dynamic environments is a fundamental problem in robotics, aiming to generate safe and efficient paths, trajectories, or control acti

safetyarxiv-cs-ro

Learning Smooth SE(3) Trajectories under Left-Invariant Riemannian Metrics

arXiv:2608.01562v1 Announce Type: new Abstract: Optimal trajectory generation for rigid-body motions on Lie groups can be formulated as a variational problem that minimizes energy functionals defined

tutorialsarxiv-cs-ro

Learning to Persuade Privately Informed Receivers

arXiv:2607.28342v1 Announce Type: cross Abstract: Bayesian persuasion studies how an informed sender can influence the behavior of a receiver through strategic information disclosure. Standard models

Mapping melliferous tree species in Kenya via one-class classification with hyperspectral unsupervised domain adaptation

arXiv:2608.02045v1 Announce Type: cross Abstract: The beekeeping sector holds significant potential for livelihood diversification among the agropastoral communities in Kenya. Melliferous tree species

Meganeura: Portable GPU Training and Inference through Vulkan and Metal

arXiv:2608.01563v1 Announce Type: new Abstract: Training and deployed inference often cross export, conversion, and platform-specific runtime boundaries. Meganeura asks whether one compact native comp

Neural Born Series Operator for Biomedical Ultrasound Computed Tomography

arXiv:2312.15575v2 Announce Type: replace-cross Abstract: Ultrasound Computed Tomography (USCT) provides a radiation-free option for high-resolution clinical imaging. Despite its potential, the comput

Neural Surrogate HMC: On Using Neural Likelihoods for Hamiltonian Monte Carlo in Simulation-Based Inference

arXiv:2407.20432v3 Announce Type: replace Abstract: Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some s

Obsidian Security raises $85M as AI agents create cybersecurity’s next major attack surface

Obsidian Security Inc. has raised an 85 million Series D funding round at a post-money valuation of 1.1 billion as enterprises increasingly look to secure autonomous artificial intelligence agents acc

agentssiliconangle

On the Viability of Semi-Supervised Segmentation Methods for Statistical Shape Modeling

model-releasesarxiv-cs-cv

arXiv:2407.15260v3 Announce Type: replace Abstract: Statistical Shape Models (SSMs) excel at identifying population level anatomical variations, which is at the core of various clinical and biomedical

OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset

arXiv:2406.14657v4 Announce Type: replace Abstract: We introduce OpenDebateEvidence, a comprehensive dataset for argument mining and summarization sourced from the American Competitive Debate communit

researcharxiv-cs-cl

Opt.Gear Technical Report

arXiv:2608.01034v1 Announce Type: new Abstract: We introduce Opt.Gear, a foundation model designed for efficient on-device deployment, real-tim inference, and strong task capability. It includes a den

Optimal Unambiguous DNFs and Alon-Saks-Seymour

arXiv:2608.02533v1 Announce Type: cross Abstract: We construct unambiguous DNFs having width O(n) but 0-certificate complexity Omega(n^2). By utilizing the special structure of these DNFs, we prove a

Optimized Piecewise Affine Abstractions of Neural Networks with Learnable Activation Functions

arXiv:2602.06737v2 Announce Type: replace Abstract: We present a generalized framework for the range verification of neural networks featuring non-linear activation functions. Our approach first const

tutorialsarxiv-cs-lg

PALMs: Using Multi Construct-Grounded Rationales for Modeling Population Preferences in LLMs

arXiv:2608.01458v1 Announce Type: new Abstract: Large language models are being extensively used to simulate individual user behavior, yet faithfully representing a population requires capturing the s

safetyarxiv-cs-cl

PartMat: Material-Aware 3D Part Decomposition with a Single Global Latent

arXiv:2608.01825v1 Announce Type: new Abstract: Part-level 3D generation has recently attracted increasing attention for producing structured and editable 3D assets. However, existing methods typicall

tutorialsarxiv-cs-cv

PhenoStitch: Training-Free Panoptic Crop Mapping from Satellite Image Time Series

arXiv:2608.00870v1 Announce Type: new Abstract: Panoptic crop mapping requires both delineating individual agricultural parcels and assigning a crop type to each parcel from satellite image time serie

Predicting Startup Exit from Textual Descriptors - A Computational Linguistics Framework

arXiv:2608.00045v1 Announce Type: new Abstract: This study shows that textual descriptors alone can predict early-stage startup success, defined as Exit, without relying on contextual, financial, or h

researcharxiv-cs-cl

Private Generative Bootstrap via Blocking

arXiv:2608.02480v1 Announce Type: cross Abstract: With AI systems gaining more access to individuals' information, it is important to protect privacy when reporting statistical answers. Equally import

Progressive^2: A Teacher-Student Progressive Co-Evolving Knowledge Distillation Method for Substantial Model Compression

arXiv:2608.00129v1 Announce Type: new Abstract: Knowledge distillation (KD) is a widely utilized technique for transferring knowledge from a large model (the teacher) to a smaller model (the student).