Search: “applications”

You Only Gaussian Once: Controllable 3D Gaussian Splatting for Ultra-Densely Sampled Scenes

model-releasesarxiv-cs-cv

arXiv:2604.21400v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has revolutionized neural rendering, yet existing methods remain predominantly research prototypes ill-suited for productio

24 Apr 2026

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ZipFold: Modular Actuators for Scaleable Adaptive Robots

DGX agent

arXiv:2604.05260v2 Announce Type: replace Abstract: There is a growing need for robots that can change their shape, size and mechanical properties to adapt to evolving tasks and environments. However,

researcharxiv-cs-ro

24 Apr 2026

A Kinematic Framework for Evaluating Pinch Configurations in Robotic Hand Design without Object or Contact Models

arXiv:2604.20692v1 Announce Type: new Abstract: Evaluating the pinch capability of a robotic hand is important for understanding its functional dexterity. However, many existing grasp evaluation metho

researcharxiv-cs-ro

Adaptive Multi-task Learning for Multi-sector Portfolio Optimization

arXiv:2507.16433v2 Announce Type: replace-cross Abstract: Accurate transfer of information across multiple sectors to enhance model estimation is both significant and challenging in multi-sector portf

Automatic Ontology Construction Using LLMs as an External Layer of Memory, Verification, and Planning for Hybrid Intelligent Systems

arXiv:2604.20795v1 Announce Type: new Abstract: This paper presents a hybrid architecture for intelligent systems in which large language models (LLMs) are extended with an external ontological memory

Calibrating conditional risk

arXiv:2604.20409v1 Announce Type: new Abstract: We introduce and study the problem of calibrating conditional risk, which involves estimating the expected loss of a prediction model conditional on inp

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment

arXiv:2510.18471v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) excel at code generation by learning from vast code corpora, a fundamental semantic gap remains between the

Coding with Eyes: Visual Feedback Unlocks Reliable GUI Code Generating and Debugging

arXiv:2604.19750v1 Announce Type: cross Abstract: Recent advances in Large Language Model (LLM)-based agents have shown remarkable progress in code generation. However, current agent methods mainly re

Context Attribution with Multi-Armed Bandit Optimization

arXiv:2506.19977v2 Announce Type: replace Abstract: Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable a

Local Ai

Decoding Text Spans for Efficient and Accurate Named-Entity Recognition

arXiv:2604.20447v1 Announce Type: new Abstract: Named Entity Recognition (NER) is a key component in industrial information extraction pipelines, where systems must satisfy strict latency and throughp

local-aiarxiv-cs-cl

Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps

arXiv:2501.07399v2 Announce Type: replace Abstract: Consistent maps are key for most autonomous mobile robots, and they often use SLAM approaches to build such maps. Loop closures via place recognitio

safetyarxiv-cs-ro

ETac: A Lightweight and Efficient Tactile Simulation Framework for Learning Dexterous Manipulation

arXiv:2604.20295v1 Announce Type: new Abstract: Tactile sensors are increasingly integrated into dexterous robotic manipulators to enhance contact perception. However, learning manipulation policies t

safetyarxiv-cs-ro

Eventually LIL Regret: Almost Sure lnln T Regret for a sub-Gaussian Mixture on Unbounded Data

arXiv:2512.12325v3 Announce Type: replace Abstract: We prove that a classic sub-Gaussian mixture proposed by Robbins in a stochastic setting actually satisfies a path-wise (deterministic) regret bound

Exploiting LLM-as-a-Judge Disposition on Free Text Legal QA via Prompt Optimization

arXiv:2604.20726v1 Announce Type: cross Abstract: This work explores the role of prompt design and judge selection in LLM-as-a-Judge evaluations of free text legal question answering. We examine wheth

Exploring High-Order Self-Similarity for Video Understanding

arXiv:2604.20760v1 Announce Type: new Abstract: Space-time self-similarity (STSS), which captures visual correspondences across frames, provides an effective way to represent temporal dynamics for vid

tutorialsarxiv-cs-cv

FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation

arXiv:2603.09046v2 Announce Type: replace-cross Abstract: Device-side Large Language Models (LLMs) have witnessed explosive growth, offering higher privacy and availability compared to cloud-side LLMs

agentsarxiv-cs-lg

From Competition to Synergy: Unlocking Reinforcement Learning for Subject-Driven Image Generation

arXiv:2510.18263v2 Announce Type: replace-cross Abstract: Subject-driven image generation models face a fundamental trade-off between identity preservation (fidelity) and prompt adherence (editability

From Ideal to Real: Stable Video Object Removal under Imperfect Conditions

arXiv:2603.09283v2 Announce Type: replace Abstract: Removing objects from videos remains difficult in the presence of real-world imperfections such as shadows, abrupt motion, and defective masks. Exis

tutorialsarxiv-cs-cv

Handbook of Rough Set Extensions and Uncertainty Models

arXiv:2604.19794v1 Announce Type: new Abstract: Rough set theory models uncertainty by approximating target concepts through lower and upper sets induced by indiscernibility, or more generally, by gra

KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devices

arXiv:2604.19834v1 Announce Type: new Abstract: Functional fitness movements are widely used in training, competition, and health-oriented exercise programs, yet consistently enforcing repetition (rep

Local Ai

Learning Spatial-Temporal Coherent Correlations for Speech-Preserving Facial Expression Manipulation

arXiv:2604.20226v1 Announce Type: new Abstract: Speech-preserving facial expression manipulation (SPFEM) aims to modify facial emotions while meticulously maintaining the mouth animation associated wi

local-aiarxiv-cs-cv

Lever: Inference-Time Policy Reuse under Support Constraints

arXiv:2604.20174v1 Announce Type: new Abstract: Reinforcement learning (RL) policies are typically trained for fixed objectives, making reuse difficult when task requirements change. We study inferenc

safetyarxiv-cs-lg

Local Diffusion Models and Phases of Data Distributions

arXiv:2508.06614v2 Announce Type: replace Abstract: As a class of generative artificial intelligence frameworks inspired by statistical physics, diffusion models have shown extraordinary performance i

tutorialsarxiv-cs-lg

MasconCube: Fast and Accurate Gravity Modeling with an Explicit Representation

arXiv:2509.08607v3 Announce Type: replace-cross Abstract: The geodesy of irregularly shaped small bodies presents fundamental challenges for gravitational field modeling, particularly as deep space ex

MetaboNet: The Largest Publicly Available Consolidated Dataset for Type 1 Diabetes Management

arXiv:2601.11505v2 Announce Type: replace-cross Abstract: Progress in Type 1 Diabetes (T1D) algorithm development is limited by the fragmentation and lack of standardization across existing T1D manage

Multi-Timescale Model Predictive Control for Slow-Fast Systems

arXiv:2511.14311v2 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) has established itself as the primary methodology for constrained control, enabling autonomy across diverse app

researcharxiv-cs-ro

On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks

arXiv:2604.20079v1 Announce Type: cross Abstract: Auto-regressive Large Language Models (LLMs) achieve strong performance on coding tasks, but incur high memory and inference costs. Diffusion-based la

researcharxiv-cs-cl

Onboard Wind Estimation for Small UAVs Equipped with Low-Cost Sensors: An Aerodynamic Model-Integrated Filtering Approach

arXiv:2604.20290v1 Announce Type: new Abstract: To enable autonomous wind estimation for energy-efficient flight in small unmanned aerial vehicles (UAVs), this study proposes a method that estimates f

agentsarxiv-cs-ro

Online Survival Analysis: A Bandit Approach under Cox PH Model

arXiv:2604.20296v1 Announce Type: cross Abstract: Survival analysis is a widely used statistical framework for modeling time-to-event data under censoring. Classical methods, such as the Cox proportio

Optimizing Data Augmentation for Real-Time Small UAV Detection: A Lightweight Context-Aware Approach

arXiv:2604.19999v1 Announce Type: new Abstract: Visual detection of Unmanned Aerial Vehicles (UAVs) is a critical task in surveillance systems due to their small physical size and environmental challe

pAI/MSc: ML Theory Research with Humans on the Loop

arXiv:2604.20622v1 Announce Type: new Abstract: We present pAI/MSc, an open-source, customizable, modular multi-agent system for academic research workflows. Our goal is not autonomous scientific idea

agentsarxiv-cs-ai

Physics-Conditioned Synthesis of Internal Ice-Layer Thickness for Incomplete Layer Traces

arXiv:2604.20783v1 Announce Type: new Abstract: Internal ice layers imaged by radar provide key evidence of snow accumulation and ice dynamics, but radar-derived layer boundary observations are often

tutorialsarxiv-cs-lg

Physics-Enhanced Deep Learning for Proactive Thermal Runaway Forecasting in Li-Ion Batteries

arXiv:2604.20175v1 Announce Type: cross Abstract: Accurate prediction of thermal runaway in lithium-ion batteries is essential for ensuring the safety, efficiency, and reliability of modern energy sto

PLR: Plackett-Luce for Reordering In-Context Learning Examples

model-releasesarxiv-cs-cl

arXiv:2603.21373v2 Announce Type: replace-cross Abstract: In-context learning (ICL) adapts large language models by conditioning on a small set of ICL examples, avoiding costly parameter updates. Amon

Rabies diagnosis in low-data settings: A comparative study on the impact of data augmentation and transfer learning

arXiv:2604.19823v1 Announce Type: cross Abstract: Rabies remains a major public health concern across many African and Asian countries, where accurate diagnosis is critical for effective epidemiologic

Real-Time Initialization of Unknown Anchors for UWB-aided Navigation

arXiv:2506.15518v2 Announce Type: replace Abstract: This paper presents a framework for the real-time initialization of unknown Ultra-Wideband (UWB) anchors in UWB-aided navigation systems. The method

agentsarxiv-cs-ro

Resolving space-sharing conflicts in road user interactions through uncertainty reduction: An active inference-based computational model

arXiv:2604.19838v1 Announce Type: new Abstract: Understanding how road users resolve space-sharing conflicts is important both for traffic safety and the safe deployment of autonomous vehicles. While

REVNET: Rotation-Equivariant Point Cloud Completion via Vector Neuron Anchor Transformer

model-releasesarxiv-cs-cv

arXiv:2601.08558v2 Announce Type: replace Abstract: Incomplete point clouds captured by 3D sensors often result in the loss of both geometric and semantic information. Most existing point cloud comple

Robustness of Spatio-temporal Graph Neural Networks for Fault Location in Partially Observable Distribution Grids

arXiv:2604.20403v1 Announce Type: new Abstract: Fault location in distribution grids is critical for reliability and minimizing outage durations. Yet, it remains challenging due to partial observabili

Rodrigues Network for Learning Robot Actions

arXiv:2506.02618v2 Announce Type: replace-cross Abstract: Understanding and predicting articulated actions is important in robot learning. However, common architectures such as MLPs and Transformers l

safetyarxiv-cs-cv

Local Ai

SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded Multimodal Named Entity Recognition

arXiv:2604.20146v1 Announce Type: cross Abstract: Grounded Multimodal Named Entity Recognition (GMNER) aims to extract named entities and localize their visual regions within image-text pairs, serving

local-aiarxiv-cs-cl

Sampling-Aware Quantization for Diffusion Models

arXiv:2505.02242v2 Announce Type: replace Abstract: Diffusion models have recently emerged as the dominant approach in visual generation tasks. However, the lengthy denoising chains and the computatio

safetyarxiv-cs-cv

scpFormer: A Foundation Model for Unified Representation and Integration of the Single-Cell Proteomics

arXiv:2604.20003v1 Announce Type: cross Abstract: The integration of single-cell proteomic data is often hindered by the fragmented nature of targeted antibody panels. To address this limitation, we i

Self-Describing Structured Data with Dual-Layer Guidance: A Lightweight Alternative to RAG for Precision Retrieval in Large-Scale LLM Knowledge Navigation

arXiv:2604.19777v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit a well-documented positional bias when processing long input contexts: information in the middle of a context win

Semantic-Fast-SAM: Efficient Semantic Segmenter

arXiv:2604.20169v1 Announce Type: new Abstract: We propose Semantic-Fast-SAM (SFS), a semantic segmentation framework that combines the Fast Segment Anything model with a semantic labeling pipeline to

Shift-Up: A Framework for Software Engineering Guardrails in AI-native Software Development -- Initial Findings

arXiv:2604.20436v1 Announce Type: cross Abstract: Generative AI (GenAI) is reshaping software engineering by shifting development from manual coding toward agent-driven implementation. While vibe codi

agentsarxiv-cs-ai

Storm Surge Modeling, Bias Correction, Graph Neural Networks, Graph Convolution Networks

arXiv:2604.20688v1 Announce Type: cross Abstract: Storm surge forecasting remains a critical challenge in mitigating the impacts of tropical cyclones on coastal regions, particularly given recent tren

Supplement Generation Training for Enhancing Agentic Task Performance

arXiv:2604.20727v1 Announce Type: cross Abstract: Training large foundation models for agentic tasks is increasingly impractical due to the high computational costs, long iteration cycles, and rapid o