Search: “research”

Decision-oriented joint optimization of evidence fusion based on event-conditioned credibility

arXiv:2504.04128v3 Announce Type: replace Abstract: In decision-level fusion tasks involving heterogeneous sources with unequal precision and potential anomalies, evidence deviating from the majority

Research

Deep learning-based hierarchical insect classification using camera trap imagery

DGX agent

arXiv:2607.28005v1 Announce Type: new Abstract: Declining insect populations make reliable biodiversity monitoring increasingly urgent, yet monitoring of insect biodiversity is hampered by a lack of s

researcharxiv-cs-cv

31 Jul 2026

Direct Rotor Thrust Sensing and Feedback Control for Disturbance Rejection of Multirotors Using Load-cells

arXiv:2607.10099v2 Announce Type: replace Abstract: Gust disturbances, dynamic vertical inflow and ground effect are key adverse aerodynamic phenomena that induce variations in the forces acting on a

researcharxiv-cs-ro

Distributions In, Distributions Out: The Case for Soft-Label Training

arXiv:2511.14117v2 Announce Type: replace Abstract: Supervised classifiers output a distribution over classes but are typically trained against a single label obtained by collapsing multiple annotator

Doubly Robust Functional Representation Learning for Longitudinal Causal Inference with Irregular Histories

arXiv:2607.28567v1 Announce Type: cross Abstract: Longitudinal causal studies often record histories as irregular functional fragments: laboratory values, physiologic signals, sensor streams, and imag

Driving up Inference Energy on SNNs: Per-Sample and Universal Sponge Attacks

arXiv:2607.27990v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) communicate through sparse binary spike events rather than dense activations, enabling energy-efficient inference on ne

ENCORE: Event-Assisted Complementary Motion Refinement for Learned Video Compression

arXiv:2607.28020v1 Announce Type: new Abstract: Learned video compression relies on accurate temporal modeling to remove redundancy between adjacent frames. However, most existing codecs infer motion

Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata

arXiv:2607.28338v1 Announce Type: new Abstract: Clustered Federated Learning (CFL) addresses data heterogeneity in federated settings by grouping clients with similar data distributions to enable effe

Endo-NeRF++: Uncertainty-Aware Neural Rendering with Multi-Resolution Hash Encoding for Dynamic Surgical Scene Reconstruction

arXiv:2607.27825v1 Announce Type: cross Abstract: Reconstructing dynamic surgical scenes is crucial for robot-assisted minimally invasive surgery; however, it continues to be difficult because of tiss

Energy-Driven Adaptive Visual Token Pruning for Efficient Vision-Language Models

arXiv:2603.05950v2 Announce Type: replace Abstract: Visual token reduction is critical for accelerating Vision-Language Models (VLMs), since visual inputs are represented as token sequences that intro

Error Analysis of Neural-Network-Based Engression

arXiv:2607.27723v1 Announce Type: cross Abstract: Engression (Shen and Meinshausen, 2024) learns a conditional distribution by fitting a generative model Y = f(X,arepsilon) under the energy score, a s

Event-Structured Physics-Informed Neural Networks for Differentiable Critical Clearing Boundaries

arXiv:2607.27681v1 Announce Type: new Abstract: Transient-stability assessment determines whether a power system can recover after a disturbance and is therefore essential to preventing generator trip

Expanding Data-Agnostic Pivotal Instances Selection Models with Proximity Trees and Ensemble Learning

arXiv:2607.27522v1 Announce Type: new Abstract: As decision-making processes grow more complex, machine learning tools have become essential for tackling business and societal challenges. However, man

Face and Voice Cross-modal Association with Learning Convex Feature Embedding

arXiv:2607.28129v1 Announce Type: new Abstract: Face-and-voice association learning is one of the most challenging tasks in deep learning. In this paper, we propose a simple but powerful cross-modal f

FADEx: Feature Attribution and Distortion-based Explanation of Dimensionality Reduction

arXiv:2607.27463v1 Announce Type: new Abstract: Dimensionality Reduction (DR) is a fundamental tool for high-dimensional data exploration, reducing the complexity of latent spaces of machine learning

FDDWAN: A Frequency-Decoupled Diffusion Network for Watermarking Attack

arXiv:2607.27800v1 Announce Type: new Abstract: Existing invisible watermark removal methods often struggle to accurately capture the watermark-bearing features, leading to an unfavorable trade-off be

FinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning

arXiv:2607.28127v1 Announce Type: new Abstract: Recent advances in Generative AI have substantially improved financial sentiment analysis through post-trained financial large language models (LLMs). H

Model Releases

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

model-releasesarxiv-cs-cl

arXiv:2607.28568v1 Announce Type: new Abstract: Recursive self-improvement (RSI) requires AI systems that improve the process of building AI (i.e., AI4AI); machine learning engineering (MLE) offers a

FunL2O: LLM-Guided Feature Function Design for Learning to Optimize

arXiv:2607.27389v1 Announce Type: new Abstract: Learning-to-optimize (L2O) methods accelerate repeated optimization by training models to predict solutions, warm starts, branching decisions, or other

Generalization Bounds on Optimal Control for Transformer Training and Wasserstein Distributional Robustness

arXiv:2607.27975v1 Announce Type: new Abstract: We derive finite-sample generalization bounds for Transformers trained with dynamic programming recursions. Building on the doubly lifted, measure-value

GGC: Selective Query Correction for Reliable Text-to-SPARQL Generation

arXiv:2607.28082v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in structured query generation, making them a natural choice for Text-to-SPARQL, whic

GLM-RAG: Graph Language Models for Graph-Based Retrieval-Augmented Generation

arXiv:2607.28397v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) over knowledge graphs requires retrievers that can effectively capture both graph structure and semantic informat

Goal-Oriented Semantic Communication for ISAC-Enabled Robotic Obstacle Avoidance

arXiv:2603.02291v2 Announce Type: replace Abstract: We investigate an integrated sensing and communication (ISAC)-enabled BS for the unmanned aerial vehicle (UAV) obstacle avoidance task, and propose

researcharxiv-cs-ro

Hallucinations Leave a Grounding Signature:Verifier-Guided Decoding for Selective Object Correction

arXiv:2607.27823v1 Announce Type: new Abstract: Large vision-language models (LVLMs) often hallucinate objects that are absent from an image. Despite recent progress, existing mitigation methods still

Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfer

arXiv:2607.28394v1 Announce Type: new Abstract: Hand-object interaction (HOI) modeling remains challenging because it requires joint reasoning about hand articulation, object geometry, contact, semant

HOMER: Huber-of-Means for Efficient and Robust Estimation in Hilbert Spaces

arXiv:2607.27532v1 Announce Type: cross Abstract: Heavy tails weaken high-confidence control for the empirical mean. Geometric median-of-means (MOM) also lacks a threshold that moves toward mean effic

How does downsampling affect needle electromyography signals? A generalisable workflow for understanding downsampling effects on high-frequency time series

arXiv:2601.10191v2 Announce Type: replace Abstract: Automated analysis of needle electromyography (nEMG) signals is emerging as a tool to support the detection of neuromuscular diseases (NMDs), yet th

Human diversity fuels collective creativity that large language models cannot simulate or sustain

arXiv:2607.26899v1 Announce Type: cross Abstract: Diverse human groups produce diverse ideas, the raw material of innovation. Generative AI challenges this engine twice over: everyday AI assistance ma

Human Mesh Modeling for Anny Body

arXiv:2511.03589v3 Announce Type: replace Abstract: Parametric body models provide the structural basis for many human-centric tasks, yet existing models often rely on costly 3D scans and learned shap

ID-Guard: A Universal Framework for Combating Facial Manipulation via Breaking Identification

arXiv:2409.13349v3 Announce Type: replace Abstract: The misuse of deep learning-based facial manipulation poses a serious threat to civil rights. To prevent such fraud at its source, proactive defense

IGME: Efficient Chained Method Ensemble for Transferable Semantic Segmentation Attacks

arXiv:2607.27465v1 Announce Type: new Abstract: Semantic segmentation models are vulnerable to transferable adversarial perturbations, yet evaluating transfer attacks on dense prediction models can be

Improved Classification of Nitrogen Stress Severity in Plants Under Combined Stress Conditions Using Spatio-Temporal Deep Learning Framework

arXiv:2509.06625v3 Announce Type: replace Abstract: Plants in their natural habitats endure an array of interacting stresses, both biotic and abiotic, that rarely occur in isolation. Nutrient stress-p

Improving Item Discoverability in e-Commerce Search via Related Intent Generation

arXiv:2607.27172v1 Announce Type: cross Abstract: Traditional search systems are optimized to retrieve items that strictly match a query, often prioritizing precision over recall. In e-commerce market

Improving Mental Health Screening and Early Risk Detection in Spanish

arXiv:2607.28476v1 Announce Type: new Abstract: Early detection of mental health disorders is often limited by the lack of specialized resources in Spanish and the difficulty of analyzing long histori

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers

arXiv:2607.27737v1 Announce Type: new Abstract: Deep neural networks (DNNs) have achieved remarkable success in classical machine learning problems. However, they are known to be vulnerable to adversa

It's All Just Vectorization: einx, a Universal Notation for Tensor Operations

arXiv:2607.27987v1 Announce Type: new Abstract: Tensor operations represent a cornerstone of modern scientific computing. However, the Numpy-like notation adopted by predominant tensor frameworks is o

Landmark shape spaces with induced metrics

arXiv:2607.28064v1 Announce Type: new Abstract: We present a unification of Kendall's landmark shape spaces, where rigid motions are factored out and scale fixed on landmark configurations equipped wi

Large scale cross-regional remote sensing flood monitoring framework for operative mapping and impact analysis

arXiv:2607.28401v1 Announce Type: new Abstract: Effective flood monitoring is critical for minimizing the impacts of flood disasters on populations and infrastructure. Yet reliable remote sensing acro

LAST: The Last Query Token Guides Visual Token Pruning for Edge-Cloud Collaborative MLLM Inference

arXiv:2607.27952v1 Announce Type: new Abstract: Multimodal foundation models are reshaping edge-cloud visual intelligence from task-specific feature pipelines into token-based interfaces, where edge d

Latent-Kernel Discrete Flow Maps for Few-Step Generation

arXiv:2607.27529v1 Announce Type: new Abstract: Discrete diffusion and flow-matching models denoise a sequence over many steps, but to keep each step cheap, they factorize the transition across positi

Latent States in Neural Networks: Recovering the Temporal Structure of Drifting Data from Model Weights

arXiv:2607.27482v1 Announce Type: cross Abstract: A temporally drifting data stream may pass through discrete regimes rather than changing continuously. We ask whether such regimes are recoverable fro

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models

arXiv:2607.28077v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models, but prompt groups with identical rol

MarkushGlyph and OCSRGlyph: Improved Chemical Structure Recognition

arXiv:2607.28532v1 Announce Type: new Abstract: Chemical structures appear in patents and the scientific literature as images. For programmatic usage, such as indexing in databases or constructing mac

Measuring Distortion in the Empty Regions of Dimensionality Reduction Scatterplots with the Gap Index

arXiv:2607.28324v1 Announce Type: new Abstract: Quality metrics play a crucial role in the proper use of dimensionality reduction projections for visual analysis of high-dimensional data. They quantif

Memory Efficient Tabular Foundation Models

arXiv:2607.27546v1 Announce Type: new Abstract: Tabular Foundation Models, such as TabPFN, have received a large amount of recent attention due to their performance on in-context tabular machine learn

MeshFM: 2D Features Are All You Need for 3D Shape Understanding

arXiv:2607.27592v1 Announce Type: new Abstract: We present MeshFM, an efficient feedforward framework for extracting rich features from 3D inputs. Our method distills 2D features from visual foundatio

Metaphor Tracer: A Theory-Informed Analysis of Hidden States

arXiv:2607.28434v1 Announce Type: cross Abstract: What do a language model's hidden states say about the organization of a single text? From one forward pass, without training, we score every token po

Meteosat Third Generation imagery improves CNN-based SSI retrieval

arXiv:2607.28093v1 Announce Type: cross Abstract: Accurate Surface Solar Irradiance (SSI) estimation is increasingly important for photovoltaic energy monitoring and forecasting. The recently introduc