research

Connected Subspace Clustering: Hardness, a Scalable Heuristic, and an Application to Sea Level Geodesy

arXiv:2608.14215v1 Announce Type: new Abstract: Constrained optimization extends classical optimization by integrating side information, making it widely applicable across scientific and engineering d

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Context Aware AI Assistant and AR Interface for Lunar Extravehicular Activity (EVA) Procedural Guidance

DGX agent

arXiv:2608.13589v1 Announce Type: cross Abstract: As human space exploration returns to the Moon, astronauts need rapid access to procedural information during extravehicular activities (EVAs), where

researcharxiv-cs-ai

17 Aug 2026

Continual Evolution Strategies in Control Tasks

arXiv:2608.13600v1 Announce Type: cross Abstract: We study Evolution Strategies (ES) for continual control, where agents must adapt to changing tasks without forgetting previous ones. On sequential Mu

Contrastive Learning for Interpretable Anomaly Detection at Collider Experiments

arXiv:2608.13652v1 Announce Type: new Abstract: Generic event-level anomaly detection for collider physics has two recurring problems: anomaly scores are hard to interpret, and they correlate strongly

CRAFT: Constrained Reward via Attention Fine-Tuning for Subject Personalization without Composed Targets

arXiv:2608.14403v1 Announce Type: new Abstract: Subject-driven image personalization---generating new images that preserve the identity of one or several reference subjects in novel scenes---is a foun

Cross-Disciplinary Taxonomy and Modeling of Misunderstanding Generation, Amplification, and Detection, from Pragmatics to AI Agents

arXiv:2608.13604v1 Announce Type: new Abstract: Detection of misunderstanding is an urgent problem to solve because communication has moved away from real-time, in-person interaction and is increasing

CSG-Mamba: A Convolutional Scoring Gating Vision State Space Network for Endoscopic Polyp Segmentation

arXiv:2608.14146v1 Announce Type: new Abstract: Accurate polyp segmentation is critical for computer-aided colonoscopy, yet endoscopic images often contain low-contrast boundaries, mucosal texture int

Data-driven techniques for translational neuroscience and personalized neuro-health

arXiv:2608.13749v1 Announce Type: cross Abstract: Neurodegenexrative diseases such as Alzheimer's disease and Parkinson's disease are diagnosed most reliably only after substantial, often irreversible

Decoding the Past: An Uncertainty-Aware Deep Learning Framework for Sex Attribution in Prehistoric Hand Stencils

arXiv:2608.14539v1 Announce Type: cross Abstract: Determining the biological sex of the individuals who created Upper Paleolithic hand stencils remains a challenging problem due to the absence of grou

Demonstration of Space Robot Teleoperation over a Lossy and Delayed Network using ATMOS

arXiv:2608.14031v1 Announce Type: new Abstract: We present a demonstration showcasing the Autonomy Testbed for Multi-purpose Orbiting Systems (ATMOS), a planar spacecraft-analog robot designed for har

researcharxiv-cs-ro

Designing Compact Neural Architectures via Neuron Gating and Mixed Activation

arXiv:2608.14443v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) is naturally formulated as a bilevel optimization problem, where the upper-level optimizes the architecture using val

Does ISO-Grounded NFR Specification Improve LLM Code Generation? A Comparison of Rich and Structured Interventions against a Natural-Language Baseline

arXiv:2608.13742v1 Announce Type: cross Abstract: In LLM-based code generation, Non-Functional Requirements (NFRs) are often specified as terse one-line phrases. We ask whether grounding those specifi

Early Stopping for Large Reasoning Models via Confidence Dynamics

arXiv:2604.04930v2 Announce Type: replace-cross Abstract: Large reasoning models rely on long chain-of-thought generation to solve complex problems, but extended reasoning often incurs substantial com

EEG-PRISM: Physiologically-Grounded Interpretability of Predictions by EEG Foundation Models

arXiv:2608.13676v1 Announce Type: new Abstract: Objective: Foundation models represent the next advancement in AI for EEG analysis; however current explainable AI techniques provide attribution scores

Emergent Models: Intelligence from Tiny Substrates

arXiv:2608.14019v1 Announce Type: cross Abstract: Emergent Models (EMs) are a machine learning paradigm based on simple yet open-ended substrates, such as cellular automata, in which modeling is treat

Face Re-morphing: Differential Morphing Attack Detection via Feature-Space Similarity Changes

arXiv:2608.13858v1 Announce Type: new Abstract: Face morphing attacks pose a serious threat to face recognition systems because a single morphed document image can be matched to multiple contributors.

Fashion Outfit Generation via Unified Sequential Composition Models

arXiv:2608.13888v1 Announce Type: new Abstract: The task of synthesizing stylistically coherent fashion outfits from massive item libraries, known as fashion outfit generation, remains a non-trivial c

Fast Implicit Neural Light Field Representation via Geometric Decomposition and Multi-Resolution Low-Rank Features

arXiv:2608.13949v1 Announce Type: new Abstract: Implicit neural representations provide a compact and continuous way to reconstruct dense light fields from sampled ray coordinates. However, fast light

Federated Prompt Learning: A Unified Framework, Empirical Analysis, and Future Directions

arXiv:2608.13844v1 Announce Type: cross Abstract: Large language models (LLMs) have become core components of cloud-based intelligent services in academia and industry, yet their training and deployme

FIRM: Fine-Grained Intra-Token Representation of Masks for Remote Sensing Reasoning Segmentation

arXiv:2608.13980v1 Announce Type: new Abstract: Reasoning segmentation requires multimodal large language models (MLLMs) to translate implicit instructions into precise pixel-level masks. MLLMs encode

FLARE MCMC: Fidelity-based Layer-Adaptive REcursive proposals for MCMC

arXiv:2608.13774v1 Announce Type: new Abstract: Markov chain Monte Carlo (MCMC) requires only the ability to evaluate the likelihood, making it a common technique for inference in complex models. Howe

FreeBalance: Pre-Routing Online Moe Load Balancing via Residual Workload Prediction

arXiv:2608.14205v1 Announce Type: new Abstract: Load imbalance poses a major bottleneck to the efficiency of expert parallelism in distributed inference of Mixture-of-Experts (MoE) models. The most he

From crown candidates to neighborhood screening: integrating optical GeoAI and spatial modeling for urban-canopy assessment in Davis, California

arXiv:2608.13856v1 Announce Type: cross Abstract: Timely urban-canopy information is essential for linking remote sensing with heat, mobility, and neighborhood planning. We developed an optical GeoAI

From Fixed Grids to Moving Particles:A Transferable Latent Operator for Fluid Dynamics

arXiv:2608.14120v1 Announce Type: cross Abstract: Lagrangian modeling is vital to fluid dynamics, as it characterizes particle transport and complements the Eulerian description.However, Lagrangian tr

From Style Replication to Style Exploration: Enabling Art Style Exploration with Analyze-Experiment-Resituate Framework

arXiv:2608.14405v1 Announce Type: cross Abstract: Art style is a signature of professional digital artists that develops through repeated experimentation, reflection, and adaptation. While generative

Generative Modeling with Bayesian Sample Inference

arXiv:2502.07580v4 Announce Type: replace Abstract: We present a novel view of diffusion-like generative modeling from the perspective of iterative Gaussian posterior inference. By treating the genera

Geometric Filtering of LLM-Generated Samples for Few-Shot Text Classification

arXiv:2608.13866v1 Announce Type: cross Abstract: Large language models (LLMs) can generate synthetic training data for text classification, but the quality of generated samples is heterogeneous: some

researcharxiv-cs-cl

Grounding Without Corrective Control: Truth-Tracking Profiles for Large Language Models

arXiv:2608.14252v1 Announce Type: new Abstract: Recent work suggests that some large language model representations have content or reference. Grounding can secure either without supplying live routes

Hard Cases, Bad Labels: Testing Error Exposure and Error Location in Uncertainty Sampling Under Bounded Label Noise

arXiv:2608.13601v1 Announce Type: new Abstract: Active learning can reduce labeling cost by selecting informative examples, but the most uncertain examples may also be the hardest to label correctly.

HI-MeshGraphNets: Efficient and Accurate Mesh-based Physics Learning with Hierarchical Multi-scale Graph Neural Networks

arXiv:2608.13827v1 Announce Type: new Abstract: Machine-learned physical surrogate models have become promising alternatives to mesh-based numerical solvers. Among them, graph neural networks (GNNs) a

Hybrid Quantum-inspired Kolmogorov-Arnold Networks for Privacy-Aware Federated Biosignal Learning

arXiv:2608.13914v1 Announce Type: cross Abstract: Electrocardiogram (ECG) recordings are sensitive biomedical data, limiting the ability of hospitals and wearable devices to share raw signals for cent

Identifiability and Order-Dimension Limits of In-Context Learning on Partial Orders

arXiv:2608.14004v1 Announce Type: new Abstract: In-context learning is commonly formalized as inference from examples of a function. Partial orders instead combine transitivity, antisymmetry, and inco

Information Satisfaction: A Reader-Centered Axis for Summarization Evaluation

arXiv:2608.14457v1 Announce Type: new Abstract: The majority of work on summarization evaluation focuses on general summary quality (e.g., ROUGE, BERTScore) or specific desired properties (e.g., reada

researcharxiv-cs-cl

Intelligent Detection of Mechanical, Electrical, and Plumbing (MEP) Metrics Based on 2D Floor Plans

arXiv:2608.14317v1 Announce Type: cross Abstract: This research developed a neural network-based model to extract various information from 2D floor plans. We detect lighting symbols, identify the appr

Interactive Analysis of Global Explanations using Aggregated Class Activation Maps for Network Data

arXiv:2608.13575v1 Announce Type: cross Abstract: Recent machine learning (ML) advances have demonstrated that deep learning (DL) achieves impressive results in different application domains, includin

Intern-S2-Mobius: Foundation Model with Decoupled Knowledge and Reasoning

arXiv:2608.14290v1 Announce Type: new Abstract: We introduce Mobius-v0, an architecture that comprises a globally shared Memory (FFN) that stores knowledge vectors and multiple Reasoners (Self-Attn) t

IterCOMP: Reasoning-aware Adaptive Prompt Compression for Multi-hop Question Answering

arXiv:2608.13588v1 Announce Type: cross Abstract: Multi-hop question answering requires complex reasoning across multiple evidence segments, which often overwhelms retrieval-augmented generation syste

Kolmogorov-Arnold Networks for Spatially Independent Multispectral Land Classification

arXiv:2608.13769v1 Announce Type: new Abstract: Land classification from satellite imagery is important for land management, environmental monitoring, and urban planning. Machine learning methods such

Label-Free Deep-Tissue Peripheral Nerve Detection with a Handheld Multimodal OCT Probe and NerveDetNet

arXiv:2608.13807v1 Announce Type: cross Abstract: Peripheral nerves buried beneath intact tissue are difficult to visualize during surgery and remain inaccessible to white light wide-field imaging and

Leading-Silence Augmentation and Multi-Stage Synthetic Supervision for the Second MLC-SLM Challenge

arXiv:2608.14150v1 Announce Type: new Abstract: The second Multilingual Conversational Speech Language Model (MLC-SLM) Challenge evaluates two tasks over complete, unsegmented multilingual conversatio

researcharxiv-cs-cl

Learning Unsteady Aneurysm Hemodynamics with Physics-Informed DeepONets

arXiv:2608.13629v1 Announce Type: cross Abstract: Clinically actionable, patient-specific hemodynamic assessment, specifically wall shear stress, vortex structure and pressure distributions, is critic

Leveraging Few-Shot Learning and Large Language Models for Analyzing Blood Pressure Variations Across Biological Sex from Scientific Literature

arXiv:2402.01826v2 Announce Type: replace-cross Abstract: Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often

LLMs Don't Pay for the Jump

arXiv:2608.14397v1 Announce Type: new Abstract: Zahavy [2026] argues that Large Language Models, despite their capabilities in induction and deduction, cannot perform the abductive 'Jump' that produce

Logarithmic Mathematical Morphology: Theory and applications

arXiv:2309.02007v3 Announce Type: replace-cross Abstract: In Mathematical Morphology for grey-level functions, an image is analysed by another image named the structuring function. This structuring fu

Lost in Phonation: Voice Quality Variation as an Evaluation Dimension for Speech Foundation Models

arXiv:2510.25577v2 Announce Type: replace-cross Abstract: Recent advances in Speech Foundation Models (SFMs) enable direct processing of raw audio, allowing models to respond to subtle paralinguistic

LP-NAS: Linear Programming-based Neural Architecture Search

arXiv:2608.14472v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) aims to automate neural network architecture design, reducing reliance on human expertise. Among the various NAS meth

Meteorology-driven Causal Nowcasting of Fugitive Landfill Emissions Enables Proactive Public Health Response

arXiv:2608.14254v1 Announce Type: cross Abstract: Fugitive emissions from waste sites increasingly expose communities to toxic and odorous gases, yet public-health responses remain largely retrospecti

Mind the Long Tail: Understanding the Difficulty of Delay Detection in Business Processes

arXiv:2608.14367v1 Announce Type: cross Abstract: The early detection of delayed cases in business processes is a critical capability for organizations. Predictive process monitoring (PPM) supports th