Search: “deployment”

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems

arXiv:2603.25749v2 Announce Type: replace-cross Abstract: Arc-fault circuit interrupters (AFCIs) are essential for mitigating fire hazards in residential photovoltaic (PV) systems, yet achieving relia

local-aiarxiv-cs-lg

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Research

A Resource-Efficient Hybrid CNN-LSTM network for image-based bean leaf disease classification

DGX agent

arXiv:2604.13835v1 Announce Type: new Abstract: Accurate and resource-efficient automated diagnosis is a cornerstone of modern agricultural expert systems. While Convolutional Neural Networks (CNNs) h

researcharxiv-cs-cv

16 Apr 2026

A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

arXiv:2604.13427v1 Announce Type: cross Abstract: Text-driven motion editing and intra-structural retargeting, where source and target share topology but may differ in bone lengths, are traditionally

Aerial Vision-Language Navigation with a Unified Framework for Spatial, Temporal and Embodied Reasoning

model-releasesarxiv-cs-cv

arXiv:2512.08639v3 Announce Type: replace Abstract: Aerial Vision-and-Language Navigation (VLN) aims to enable unmanned aerial vehicles (UAVs) to interpret natural language instructions and navigate c

Artificial intelligence application in lymphoma diagnosis with Vision Transformer using weakly supervised training

arXiv:2604.13795v1 Announce Type: new Abstract: Vision transformers (ViT) have been shown to allow for more flexible feature detection and can outperform convolutional neural network (CNN) when pre-tr

BenGER: A Collaborative Web Platform for End-to-End Benchmarking of German Legal Tasks

arXiv:2604.13583v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for legal reasoning requires workflows that span task design, expert annotation, model execution, and metric-bas

Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference

arXiv:2604.13634v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by letting draft tokens bypass full verification, but conventional frameworks suffer from fre

researcharxiv-cs-cl

Deep Learning Based Amharic Chatbot for FAQs in Universities

arXiv:2402.01720v3 Announce Type: replace-cross Abstract: University students often spend a considerable amount of time seeking answers to common questions from administrators or teachers. This can be

researcharxiv-cs-cl

DeEscalWild: A Real-World Benchmark for Automated De-Escalation Training with SLMs

arXiv:2604.13075v1 Announce Type: new Abstract: Effective de-escalation is critical for law enforcement safety and community trust, yet traditional training methods lack scalability and realism. While

Driving Engagement in Daily Fantasy Sports with a Scalable and Urgency-Aware Ranking Engine

arXiv:2604.13796v1 Announce Type: cross Abstract: In daily fantasy sports (DFS), match participation is highly time-sensitive. Users must act within a narrow window before a game begins, making match

local-aiarxiv-cs-lg

Event-Adaptive State Transition and Gated Fusion for RGB-Event Object Tracking

arXiv:2604.13426v1 Announce Type: new Abstract: Existing Vision Mamba-based RGB-Event(RGBE) tracking methods suffer from using static state transition matrices, which fail to adapt to variations in ev

Explainable Fall Detection for Elderly Care via Temporally Stable SHAP in Skeleton-Based Human Activity Recognition

arXiv:2604.13279v1 Announce Type: new Abstract: Fall detection in elderly care requires not only accurate classification but also reliable explanations that clinicians can trust. However, existing pos

local-aiarxiv-cs-cv

Exposia: Teaching and Assessment of Academic Writing Skills for Research Project Proposals and Peer Feedback

arXiv:2601.06536v2 Announce Type: replace Abstract: We present Exposia, the first public dataset that connects writing and feedback in higher education, enabling research on educationally grounded com

Applications

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective

arXiv:2604.14025v1 Announce Type: new Abstract: Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and i

applicationsarxiv-cs-cv

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments

arXiv:2508.08791v3 Announce Type: replace Abstract: Effective tool use is essential for large language models (LLMs) to interact with their environment. However, progress is limited by the lack of eff

local-aiarxiv-cs-cl

FiLM-Nav: Efficient and Generalizable Navigation via VLM Fine-tuning

model-releasesarxiv-cs-ro

arXiv:2509.16445v2 Announce Type: replace Abstract: Enabling robotic assistants to navigate complex environments and locate objects described in free-form language is a critical capability for real-wo

Applications

From Relevance to Authority: Authority-aware Generative Retrieval in Web Search Engines

arXiv:2604.13468v1 Announce Type: cross Abstract: Generative information retrieval (GenIR) formulates the retrieval process as a text-to-text generation task, leveraging the vast knowledge of large la

applicationsarxiv-cs-cl

Geminet: Learning the Duality-based Iterative Process for Lightweight Traffic Engineering in Changing Topologies

arXiv:2506.23640v2 Announce Type: replace-cross Abstract: Recently, researchers have explored ML-based Traffic Engineering (TE), leveraging neural networks to solve TE problems traditionally addressed

Hybrid Retrieval for COVID-19 Literature: Comparing Rank Fusion and Projection Fusion with Diversity Reranking

arXiv:2604.13728v1 Announce Type: cross Abstract: We present a hybrid retrieval system for COVID-19 scientific literature, evaluated on the TREC-COVID benchmark (171,332 papers, 50 expert queries). Th

LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks

arXiv:2604.13072v1 Announce Type: new Abstract: LLM-based agents are increasingly expected to handle real-world assistant tasks, yet existing benchmarks typically evaluate them under isolated sources

Lossless Prompt Compression via Dictionary-Encoding and In-Context Learning: Enabling Cost-Effective LLM Analysis of Repetitive Data

arXiv:2604.13066v1 Announce Type: new Abstract: In-context learning has established itself as an important learning paradigm for Large Language Models (LLMs). In this paper, we demonstrate that LLMs c

MedRCube: A Multidimensional Framework for Fine-Grained and In-Depth Evaluation of MLLMs in Medical Imaging

arXiv:2604.13756v1 Announce Type: new Abstract: The potential of Multimodal Large Language Models (MLLMs) in domain of medical imaging raise the demands of systematic and rigorous evaluation framework

Multi-Agent Object Detection Framework Based on Raspberry Pi YOLO Detector and Slack-Ollama Natural Language Interface

arXiv:2604.13345v1 Announce Type: new Abstract: The paper presents design and prototype implementation of an edge based object detection system within the new paradigm of AI agents orchestration. It g

local-aiarxiv-cs-cv

Multi-Task LLM with LoRA Fine-Tuning for Automated Cancer Staging and Biomarker Extraction

model-releasesarxiv-cs-lg

arXiv:2604.13328v1 Announce Type: new Abstract: Pathology reports serve as the definitive record for breast cancer staging, yet their unstructured format impedes large-scale data curation. While Large

Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities

arXiv:2602.07924v2 Announce Type: replace Abstract: Securing petroleum infrastructure requires balancing autonomous system efficiency with human judgment for threat escalation, a challenge unaddressed

agentsarxiv-cs-ro

Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference

model-releasesarxiv-cs-lg

arXiv:2604.13252v1 Announce Type: new Abstract: Anomaly detection aims to identify observations that deviate from expected behavior. Because anomalous events are inherently sparse, most frameworks are

QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs

arXiv:2604.13786v1 Announce Type: new Abstract: As large language models become standard backends for content generation, practical provenance increasingly requires multi-bit watermarking. In provider

researcharxiv-cs-cl

Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors

arXiv:2604.13951v1 Announce Type: new Abstract: This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analy

See&Say: Vision Language Guided Safe Zone Detection for Autonomous Package Delivery Drones

arXiv:2604.13292v1 Announce Type: new Abstract: Autonomous drone delivery systems are rapidly advancing, but ensuring safe and reliable package drop-offs remains highly challenging in cluttered urban

safetyarxiv-cs-cv

Simulation-Based Optimisation of Batting Order and Bowling Plans in T20 Cricket

arXiv:2604.13861v1 Announce Type: new Abstract: This paper develops a unified Markov Decision Process (MDP) framework for optimising two recurring in-match decisions in T20 cricket namely batting orde

UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception

arXiv:2604.14089v1 Announce Type: new Abstract: We present UMI-3D, a multimodal extension of the Universal Manipulation Interface (UMI) for robust and scalable data collection in embodied manipulation

safetyarxiv-cs-ro

VIGILant: an automatic classification pipeline for glitches in the Virgo detector

arXiv:2604.13687v1 Announce Type: cross Abstract: Glitches frequently contaminate data in gravitational-wave detectors, complicating the observation and analysis of astrophysical signals. This work in

WebXSkill: Skill Learning for Autonomous Web Agents

arXiv:2604.13318v1 Announce Type: cross Abstract: Autonomous web agents powered by large language models (LLMs) have shown promise in completing complex browser tasks, yet they still struggle with lon

agentsarxiv-cs-cl

WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain

arXiv:2604.13055v1 Announce Type: new Abstract: Today's evolving labor markets rely increasingly on recommender systems for hiring, talent management, and workforce analytics, with natural language pr

ZK-APEX: Zero-Knowledge Approximate Personalized Unlearning with Executable Proofs

arXiv:2512.09953v2 Announce Type: replace-cross Abstract: Machine unlearning aims to remove the influence of specific data points from a trained model to satisfy privacy, copyright, and safety require

safetyarxiv-cs-lg

A Dataset and Evaluation for Complex 4D Markerless Human Motion Capture

arXiv:2604.12765v1 Announce Type: new Abstract: Marker-based motion capture (MoCap) systems have long been the gold standard for accurate 4D human modeling, yet their reliance on specialized hardware

safetyarxiv-cs-cv

Adaptive Budget Allocation in LLM-Augmented Surveys

arXiv:2604.12497v1 Announce Type: new Abstract: Large language models (LLMs) can generate survey responses at low cost, but their reliability varies substantially across questions and is unknown befor

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI

arXiv:2603.18104v3 Announce Type: replace Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relat

researcharxiv-cs-ai

Agentic LLM Reasoning in a Self-Driving Laboratory for Air-Sensitive Lithium Halide Spinel Conductors

arXiv:2604.11957v1 Announce Type: cross Abstract: Self-driving laboratories promise to accelerate materials discovery. Yet current automated solid-state synthesis platforms are limited to ambient cond

agentsarxiv-cs-lg

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods

arXiv:2603.21011v2 Announce Type: replace-cross Abstract: Finite element (FE) analysis guides the design and verification of nearly all manufactured objects. It is at the core of computational enginee

agentsarxiv-cs-ai

Beyond Static Sandboxing: Learned Capability Governance for Autonomous AI Agents

arXiv:2604.11839v1 Announce Type: cross Abstract: Autonomous AI agents built on open-source runtimes such as OpenClaw expose every available tool to every session by default, regardless of the task. A

safetyarxiv-cs-ai

Applications

BINDER: Instantly Adaptive Mobile Manipulation with Open-Vocabulary Commands

arXiv:2511.22364v2 Announce Type: replace-cross Abstract: Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their worl

applicationsarxiv-cs-ai

Boosting Robust AIGI Detection with LoRA-based Pairwise Training

arXiv:2604.12307v1 Announce Type: new Abstract: The proliferation of highly realistic AI-Generated Image (AIGI) has necessitated the development of practical detection methods. While current AIGI dete

CBAM-Enhanced DenseNet121 for Multi-Class Chest X-Ray Classification with Grad-CAM Explainability

arXiv:2604.12305v1 Announce Type: cross Abstract: Pneumonia remains a leading cause of childhood mortality worldwide, with a heavy burden in low-resource settings such as Bangladesh where radiologist

CoD-Lite: Real-Time Diffusion-Based Generative Image Compression

model-releasesarxiv-cs-cv

arXiv:2604.12525v1 Announce Type: new Abstract: Recent advanced diffusion methods typically derive strong generative priors by scaling diffusion transformers. However, scaling fails to generalize when

DeferredSeg: A Multi-Expert Deferral Framework for Trustworthy Medical Image Segmentation

arXiv:2604.12411v1 Announce Type: new Abstract: Segmentation models based on deep neural networks demonstrate strong generalization for medical image segmentation. However, they often exhibit overconf

Dynamic Modeling and Robust Gait Optimization of a Compliant Worm Robot

arXiv:2604.12031v1 Announce Type: new Abstract: Worm-inspired robots provide an effective locomotion strategy for constrained environments by combining cyclic body deformation with alternating anchori

researcharxiv-cs-ro

Fragile Reconstruction: Adversarial Vulnerability of Reconstruction-Based Detectors for Diffusion-Generated Images

arXiv:2604.12781v1 Announce Type: new Abstract: Recently, detecting AI-generated images produced by diffusion-based models has attracted increasing attention due to their potential threat to safety. A

safetyarxiv-cs-cv