Search: “research”

Geometry-Aware Visual Odometry for Bronchoscopic Navigation via High-Gain Observer Fusion

arXiv:2607.05162v1 Announce Type: new Abstract: Navigational bronchoscopy is critical for pulmonary interventions, yet current platforms depend heavily on pre-operative CT or external sensors, limitin

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GeoSAM-Lite: A Lightweight Foundation Model for Onboard Remote Sensing Segmentation

DGX agent

arXiv:2607.03760v1 Announce Type: new Abstract: The deployment of large-scale foundation models like Segment Anything Model (SAM) on resource-constrained Earth observation platforms is hindered by pro

researcharxiv-cs-cv

7 Jul 2026

GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Text

arXiv:2312.15320v3 Announce Type: replace-cross Abstract: Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests, and genetic

GlacierCastAI: Predicting Glacier Retreat from Multi-Modal Satellite Imagery and Climate Signals

arXiv:2607.04117v1 Announce Type: cross Abstract: ERA5 seasonal climate variables contain predictive information about future glacier retreat beyond what satellite imagery alone provides, yet existing

GlaKG: A Biomarker-Centric Fundus Knowledge Graph for Explainable Glaucoma Diagnosis and Risk Assessment

arXiv:2607.04673v1 Announce Type: new Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer lit

Glance-Say: Multimodal Human-Robot Collaboration and Intent Recognition via Sticky Glance

arXiv:2603.06121v2 Announce Type: replace Abstract: Gaze and speech are promising interaction modalities for individuals with motor impairments, yet robust intent recognition in multi-object environme

researcharxiv-cs-ro

Global Pose Control for Generative View Synthesis in Normalized Object Coordinate Space

arXiv:2607.02712v1 Announce Type: new Abstract: Novel View Synthesis (NVS) enables the generation of unseen views of a scene from a single or multiple images, allowing users to freely explore an objec

Global universal approximation with Brownian signatures

arXiv:2512.16396v2 Announce Type: replace-cross Abstract: We establish L^p-universal approximation theorems for general path-dependent and non-anticipative functionals on suitable rough path spaces, s

Gradient Descent as Implicit EM in Distance-Based Neural Models

arXiv:2512.24780v2 Announce Type: replace Abstract: Neural networks trained with standard objectives exhibit behaviors characteristic of probabilistic inference: soft clustering, prototype specializat

Granger Causality in Extremes

arXiv:2407.09632v3 Announce Type: replace-cross Abstract: We introduce a rigorous mathematical framework for Granger causality in extremes, designed to identify causal links from extreme events in tim

Graph Unitary Message Passing

arXiv:2403.11199v2 Announce Type: replace-cross Abstract: Unitarity is a useful principle for stabilizing deep neural networks, but in graph neural networks (GNNs) instability is induced not only by l

GRASP: Graph-Reasoning Aided Survey Planning for High-Fidelity Related Work Generation

arXiv:2607.03709v1 Announce Type: new Abstract: Writing a literature review requires a deep understanding of the relationships among cited papers: how they build on, challenge, or offer alternative pe

Green for Go, Red for No: Visual Grounding via Semantic Segmentation for VLA Navigation Policies

arXiv:2607.05122v1 Announce Type: new Abstract: Vision-language-action (VLA) models enable robot navigation from natural language and visual goals, but remain susceptible to perceptual distractions an

GUSH3R: Everyone Everywhere All at Once as Gaussians

arXiv:2607.05243v1 Announce Type: new Abstract: Reconstructing dynamic human-scene environments from monocular videos is a challenging problem that requires jointly modeling scene geometry, camera mot

Handwriting Trajectory Recovery with Diffusion Models

arXiv:2607.03422v1 Announce Type: new Abstract: Recovering online pen trajectories from offline handwriting images, often referred to as handwriting trajectory recovery (stroke recovery), is an offlin

HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopy

arXiv:2607.04353v1 Announce Type: cross Abstract: Hierarchical structure is common in image data, where fine-grained clusters often merge into larger, coarser semantic groups. In biological cell image

Heterogeneous Graph Condensation via Role-Aware Clustering

arXiv:2607.03097v1 Announce Type: new Abstract: Heterogeneous Graph Neural Networks (HGNNs) have exhibited remarkable efficacy in modeling complex systems with multiple types of nodes and relations, y

Hierarchical Evidence-Driven Reasoning for Long Document Understanding

arXiv:2607.04625v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) streamlines long-document understanding by leveraging retrieval mechanisms to restrict input images to a highly c

Hierarchical Sparse Attention Done Right: Toward Infinite Context Modeling

arXiv:2607.02980v1 Announce Type: cross Abstract: Scaling modern large language models (LLMs) to long contexts is limited by the quadratic computation cost, and poor length extrapolation of dense atte

HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control

arXiv:2607.03449v1 Announce Type: cross Abstract: Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and r

How Many Initial Points Does Bayesian Optimization Need?

arXiv:2607.04356v1 Announce Type: new Abstract: Bayesian Optimization (BO) generally begins with an initialization phase: a batch of n_0 uninformed evaluations. The choice of n_0 remains largely heuri

Hyperparameter Transfer in Graph Neural Networks

arXiv:2607.05017v1 Announce Type: cross Abstract: The performance of deep learning models crucially depends on the settings of hyperparameters like learning rate, initialization scale, and weight deca

iFLYTEK-Embodied-Omni Technical Report

arXiv:2607.02542v1 Announce Type: new Abstract: General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actio

Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent

arXiv:2409.08469v4 Announce Type: replace-cross Abstract: We provide finite-particle convergence rates for the Stein Variational Gradient Descent (SVGD) algorithm in the Kernelized Stein Discrepancy (

Improved generalization bounds for binary linear classification via isoperimetry

arXiv:2505.16713v3 Announce Type: replace-cross Abstract: We examine the concentration of uniform generalization errors around their expectation in binary linear classification problems via an isoperi

In-span learning: adapting reduced-order models using their own predictions

arXiv:2607.02937v1 Announce Type: new Abstract: Reduced-order models compress high-dimensional dynamics into low-dimensional representations that can be evaluated rapidly, but they lose accuracy when

Inclusive KL Gradient Flows: Otto-Wasserstein, Fisher-Rao-Gaussian, and Local-Estimator Dynamics

arXiv:2411.00214v2 Announce Type: replace-cross Abstract: Otto's Wasserstein gradient flow of the inclusive (forward) Kullback--Leibler (KL) divergence offers a principled framework for analyzing stat

Individual Parameters in Weight-Sparse Transformers Appear Interpretable

arXiv:2607.02964v1 Announce Type: cross Abstract: A central goal of mechanistic interpretability is to understand how neural networks work and what each individual component does. Dominant circuit-fin

Inelastic Constitutive Kolmogorov-Arnold Networks: A generalized framework for automated discovery of interpretable inelastic material models

arXiv:2602.17750v2 Announce Type: replace-cross Abstract: A key problem of solid mechanics is the identification of the constitutive law of a material, that is, the relation between strain history and

Information-Geometric Superposed Vowel Evaluation: Part 1. Moraic Syllabary (Japanese)

arXiv:2607.04154v1 Announce Type: cross Abstract: This paper explains the principles and provides examples of a new method for distinguishing between FAKE human speech synthesized by generative AI and

InSpace: Structure-Aware 3D Indoor Scene Generation from a Single 360{eg} Image

arXiv:2607.03990v1 Announce Type: new Abstract: Recent advances in single image-to-3D generation have enabled high-quality asset synthesis, yet extending these capabilities to indoor scene generation

Integrated Forward-Inverse Network for Lensless Image Reconstruction

arXiv:2607.04608v1 Announce Type: new Abstract: Lensless imaging enables compact and versatile computational cameras by replacing bulky optics with thin coded elements. However, reconstruction from th

Interaction Techniques that Encourage Longer Prompts Can Improve Psychological Ownership when Writing with AI

arXiv:2507.03670v2 Announce Type: replace-cross Abstract: Writing longer prompts for an AI assistant to generate a story increases psychological ownership, a user's feeling that the writing belongs to

Interpretable machine learning predicts Parkinson's disease severity using motion-corrected QSM MRI and multiband multiecho fMRI features

arXiv:2607.02553v1 Announce Type: new Abstract: Introduction: Objective neuroimaging biomarkers may improve Parkinson's disease motor assessment by capturing brain variation not directly observable fr

Inverse Design of Metainterfaces for Static Friction Control: Beyond the Hertzian Limit

arXiv:2605.11012v2 Announce Type: cross Abstract: Programming the static friction of mechanical interfaces is critical for soft robotics, haptics, and precision gripping. Static friction is governed b

InverseCrafter: Efficient Video ReCapture as a Latent Domain Inverse Problem

arXiv:2512.05672v2 Announce Type: replace-cross Abstract: Recent approaches in controllable novel view video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This domina

Is Generation Required for Data-Efficient Perception?

arXiv:2512.08854v3 Announce Type: replace Abstract: It has been hypothesized that achieving the data efficiency of human visual perception requires a generative approach in which internal representati

It's all In the (Exponential) Family: An Equivalence between Maximum Likelihood Estimation and Control Variates for Sketching Algorithms

arXiv:2601.22378v3 Announce Type: replace-cross Abstract: Maximum likelihood estimators (MLE) and control variate estimators (CVE) have been used in conjunction with known information across sketching

Jointly Improving Dialect Identification and ASR in Indian Languages using Multimodal Feature Fusion

arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of which are low-resource and exhibit signifi

KAN vs LSTM Performance in Time Series Forecasting

arXiv:2511.18613v2 Announce Type: replace-cross Abstract: This study presents a controlled comparison of baseline Kolmogorov-Arnold Networks (KAN), implemented via PyKAN, and Long Short-Term Memory (L

KinEMbed: Decoding Kinematics from Electromyography via Cross-Modal Contrastive Learning

arXiv:2607.04820v1 Announce Type: new Abstract: Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthetic

Knowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMs

arXiv:2607.05013v1 Announce Type: new Abstract: Although LLMs have made significant progress in mathematical reasoning, determining whether a mathematical problem is solvable remains a fundamental yet

Language Generation with Replay: A Learning-Theoretic View of Model Collapse

arXiv:2603.11784v2 Announce Type: replace Abstract: As scaling laws push the training of frontier large language models (LLMs) toward ever-growing data requirements, training pipelines are approaching

Language Models as Higher-Order Planning Formalizers

arXiv:2603.23844v2 Announce Type: replace Abstract: Recent work provides overwhelming evidence that LLMs, even those trained to scale their reasoning trace, quickly deteriorate at planning as problems

Language Models Represent and Transform Concepts with Shared Geometry

arXiv:2607.04525v1 Announce Type: cross Abstract: How concepts are represented in neural networks is a fundamental question in machine learning. The dominant view treats concept representations as sta

LAW & ORDER: Adaptive Spatial Weighting for Medical Diffusion and Segmentation

arXiv:2603.04795v2 Announce Type: replace-cross Abstract: Medical image analysis depends on accurate segmentation and controllable synthesis, but both tasks face severe spatial imbalance: lesions occu

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers

arXiv:2607.04819v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) enables computation on encrypted data, but practical encrypted Transformer inference is bottlenecked by the sequentia

LBTCap: A Lightweight Bilateral Transformer for Real-Time Remote Sensing Image Change Captioning

arXiv:2607.03320v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) generates natural-language descriptions of semantic changes between paired remote sensing images (RSIs),