Search: “papers”

Digitizing Nepal's Written Heritage: A Comprehensive HTR Pipeline for Old Nepali Manuscripts

arXiv:2512.17111v2 Announce Type: replace Abstract: This paper presents the first end-to-end pipeline for Handwritten Text Recognition (HTR) for Old Nepali, a historically significant but low-resource

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Enhancing Financial Report Question-Answering: A Retrieval-Augmented Generation System with Reranking Analysis

DGX agent

arXiv:2603.16877v2 Announce Type: replace Abstract: Financial analysts face significant challenges extracting information from lengthy 10-K reports, which often exceed 100 pages. This paper presents a

model-releasesarxiv-cs-cl

29 Apr 2026

Knowledge Distillation Must Account for What It Loses

arXiv:2604.25110v1 Announce Type: new Abstract: This position paper argues that knowledge distillation must account for what it loses: student models should be judged not only by retained task scores,

Measuring the Sensitivity of Classification Models with the Error Sensitivity Profile

arXiv:2604.25765v1 Announce Type: new Abstract: The quality of training data is critical to the performance of machine learning models. In this paper, the Error Sensitivity Profile (ESP) is proposed.

NimbleReg: A light-weight deep-learning framework for diffeomorphic image registration

arXiv:2503.07768v2 Announce Type: replace Abstract: This paper presents NimbleReg, a light-weight deep-learning (DL) framework for diffeomorphic image registration leveraging surface representation of

safetyarxiv-cs-cv

Self-DACE++: Robust Low-Light Enhancement via Efficient Adaptive Curve Estimation

model-releasesarxiv-cs-cv

arXiv:2604.25367v1 Announce Type: new Abstract: In this paper, we present Self-DACE++, an improved unsupervised and lightweight framework for Low-Light Image Enhancement (LLIE), building upon our prev

Sensitivity-Based Tube NMPC for Cooperative Aerial Structures Under Parametric Uncertainty

arXiv:2604.25766v1 Announce Type: new Abstract: This paper presents a sensitivity-based tube Nonlinear Model Predictive Control (NMPC) framework for cooperative aerial chains under bounded parametric

Slot-hopping Enabled Loiter Guidance and Automation for Fixed-wing UAV Corridors

arXiv:2604.25292v1 Announce Type: new Abstract: This paper addresses the problem of traffic congestion management in fixed-wing unmanned aerial vehicle (UAV) corridors by further developing a recently

StrADiff: A Structured Source-Wise Adaptive Diffusion Framework for Linear and Nonlinear Blind Source Separation

arXiv:2604.04973v2 Announce Type: replace-cross Abstract: This paper presents StrADiff, a Structured Source-Wise Adaptive Diffusion Framework for unsupervised blind source separation under linear and

Hardware

Tendon-Actuated Robots with a Tapered, Flexible Polymer Backbone: Design, Fabrication, and Modeling

arXiv:2603.19124v2 Announce Type: replace Abstract: This paper presents the design, modeling, and fabrication of 3D-printed, tendon-actuated continuum robots featuring a flexible, tapered backbone con

hardwarearxiv-cs-ro

A Divergence-Based Method for Weighting and Averaging Model Predictions

arXiv:2604.24172v1 Announce Type: cross Abstract: This paper uses a minimum divergence framework to introduce a new way of calculating model weights that can be used to average probabilistic predictio

A Layer Separation Optimization Framework for Cross-Entropy Training in Deep Learning

arXiv:2604.23225v1 Announce Type: new Abstract: This paper investigates the deep learning optimization problem with softmax cross-entropy loss. We propose a layer separation strategy to alleviate the

Agent-Aided Design for Dynamic CAD Models

arXiv:2604.15184v2 Announce Type: replace Abstract: In the past year, researchers have created agentic systems that can design real-world CAD-style objects in a training-free setting, a new variety of

agentsarxiv-cs-ai

Applications of the Transformer Architecture in AI-Assisted English Reading Comprehension

arXiv:2604.23615v1 Announce Type: cross Abstract: This paper studies interpretable and fair artificial intelligence architectures for understanding English reading. Introduced transformer-based models

Attention-Augmented YOLOv8 with Ghost Convolution for Real-Time Vehicle Detection in Intelligent Transportation Systems

arXiv:2604.22856v1 Announce Type: new Abstract: Accurate vehicle detection is a critical component of autonomous driving, traffic surveillance, and intelligent transportation systems. This paper prese

agentsarxiv-cs-cv

Local Ai

Benchmarking Source-Sensitive Reasoning in Turkish: Humans and LLMs under Evidential Trust Manipulation

arXiv:2604.24665v1 Announce Type: cross Abstract: This paper investigates whether source trustworthiness shapes Turkish evidential morphology and whether large language models (LLMs) track this sensit

local-aiarxiv-cs-ai

Betting for Sim-to-Real Performance Evaluation

arXiv:2604.24018v1 Announce Type: new Abstract: This paper studies the problem of robot performance evaluation, focusing on how to obtain accurate and efficient estimates of real-world behavior under

safetyarxiv-cs-ro

Applications

Collocation-based Robust Physics Informed Neural Networks for time-dependent simulations of pollution propagation under thermal inversion conditions on Spitsbergen

arXiv:2604.23003v1 Announce Type: new Abstract: In this paper, we propose a Physics-Informed Neural Network framework for time-dependent simulations of pollution propagation originating from moving em

applicationsarxiv-cs-lg

Conflict-Aware Harmonized Rotational Gradient for Multiscale Kinetic Regimes

arXiv:2604.24745v1 Announce Type: new Abstract: In this paper, we propose a harmonized rotational gradient method, termed HRGrad, for simultaneously tackling multiscale time-dependent kinetic problems

Diffusion Model as a Generalist Segmentation Learner

arXiv:2604.24575v1 Announce Type: new Abstract: Diffusion models are primarily trained for image synthesis, yet their denoising trajectories encode rich, spatially aligned visual priors. In this paper

researcharxiv-cs-cv

DNNs, Dataset Statistics, and Correlation Functions

arXiv:2511.21715v2 Announce Type: replace-cross Abstract: This paper argues that dataset structure is important in image recognition tasks (among other tasks). Specifically, we focus on the nature and

DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute

arXiv:2604.23815v1 Announce Type: new Abstract: Scientific Deep Research (DR) agents answer user queries by synthesizing research papers into multi-section reports. User feedback can improve their uti

agentsarxiv-cs-cl

DriVerse: Navigation World Model for Driving Simulation via Multimodal Trajectory Prompting and Motion Alignment

model-releasesarxiv-cs-ro

arXiv:2504.18576v2 Announce Type: replace Abstract: This paper presents DriVerse, a generative model for simulating navigation-driven driving scenes from a single image and a future trajectory. Previo

Tutorials

Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook

arXiv:2406.05984v2 Announce Type: replace-cross Abstract: Mental health constitutes a complex and pervasive global challenge, affecting millions of lives and often leading to severe consequences. In t

tutorialsarxiv-cs-ai

Failure-Centered Runtime Evaluation for Deployed Trilingual Public-Space Agents

arXiv:2604.23990v1 Announce Type: new Abstract: This paper presents PSA-Eval, a failure-centered runtime evaluation framework for deployed trilingual public-space agents. The central claim is that, wh

safetyarxiv-cs-ai

From Stateless Queries to Autonomous Actions: A Layered Security Framework for Agentic AI Systems

arXiv:2604.23338v1 Announce Type: cross Abstract: Agentic AI systems face security challenges that stateless large language models do not. They plan across extended horizons, maintain persistent memor

Generating Place-Based Compromises Between Two Points of View

model-releasesarxiv-cs-cl

arXiv:2604.24536v1 Announce Type: new Abstract: Large Language Models (LLMs) excel academically but struggle with social intelligence tasks, such as creating good compromises. In this paper, we presen

Hierarchical RL-MPC Control for Dynamic Wake Steering in Wind Farms

arXiv:2604.22797v1 Announce Type: cross Abstract: Wind farm wake steering optimization is challenging due to complex flow physics and changing conditions. This paper presents a hierarchical framework

Human-AI Governance (HAIG): A Trust-Utility Approach

arXiv:2505.01651v4 Announce Type: replace Abstract: This paper introduces the Human-AI Governance (HAIG) framework, contributing to the AI Governance (AIG) field by foregrounding the relational dynami

agentsarxiv-cs-ai

Identifiability and Stability of Generative Drifting with Companion-Elliptic Kernel Families

arXiv:2604.24196v1 Announce Type: cross Abstract: This paper analyzes identifiability and stability for the drifting field underlying distributional matching in the Generative Drifting framework of De

ImmerIris: A Large-Scale Dataset and Benchmark for Off-Axis and Unconstrained Iris Recognition in Immersive Applications

model-releasesarxiv-cs-cv

arXiv:2510.10113v3 Announce Type: replace Abstract: Recently, iris recognition is regaining prominence in immersive applications such as extended reality as a means of seamless user identification. Th

Infrastructure-Guided Connectivity-Enhanced Road Crack Detection and Estimation

arXiv:2604.24616v1 Announce Type: new Abstract: In this paper, we report the world's first infrastructure-guided communication-enhanced road crack detection pipeline that is effective and implementabl

researcharxiv-cs-cv

Applications

IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0

arXiv:2604.22857v1 Announce Type: new Abstract: This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional ne

applicationsarxiv-cs-cv

Hardware

Latent Inter-Frame Pruning: A Training-Free Method Bridging Traditional Video Compression and Modern Diffusion Transformers for Efficient Generation

arXiv:2604.23858v1 Announce Type: new Abstract: Video generation, while capable of generating realistic videos, is computationally expensive and slow, prohibiting real-time applications. In this paper

hardwarearxiv-cs-cv

LatentBurst: A Fast and Efficient Multi Frame Super-Resolution for Hexadeca-Bayer Pattern CIS images

arXiv:2604.23268v1 Announce Type: new Abstract: This paper introduces a novel multi frame super-resolution network (MFSR) for burst hexadeca Bayer pattern Contact Image Sensor (CIS) images, which incl

researcharxiv-cs-cv

Tutorials

Learn&Drop: Fast Learning of CNNs based on Layer Dropping

arXiv:2604.23403v1 Announce Type: cross Abstract: This paper proposes a new method to improve the training efficiency of deep convolutional neural networks. During training, the method evaluates score

tutorialsarxiv-cs-ai

LLM-Assisted Op-Amp Behavioral-Level Design via Agentic Human-Mimicking Reasoning

arXiv:2601.21321v2 Announce Type: replace Abstract: This paper proposes White-Op, an operational amplifier (op-amp) behavioral-level parameter design framework assisted by the human-mimicking reasonin

LLM4SCREENLIT: Recommendations on Assessing the Performance of Large Language Models for Screening Literature in Systematic Reviews

arXiv:2511.12635v2 Announce Type: replace-cross Abstract: Context: Large language models (LLMs) are increasingly used to screen literature for systematic reviews (SRs), but the standard confusion-matr

Multi-Robot Motions in Milliseconds: Vector-Accelerated Primitives for Sampling-Based Planning

arXiv:2604.23960v1 Announce Type: new Abstract: In this paper, we extend the recent Vector-Accelerated Motion Planning (VAMP) framework to multi-robot motion planning (MRMP). We develop two vector-acc

Muscle Coactivation in the Sky: Geometry and Pareto Optimality of Energy vs. Aerodynamic Promptness and Multirotors as Variable Stiffness Actuators

arXiv:2602.14222v2 Announce Type: replace Abstract: In robotics and biomechanics, trading metabolic cost for kinematic readiness is a well-established principle. This paper formalizes this concept for

On-Device Vision Training, Deployment, and Inference on a Thumb-Sized Microcontroller

model-releasesarxiv-cs-cv

arXiv:2604.23012v1 Announce Type: cross Abstract: This paper presents a complete, end-to-end on-device vision machine learning pipeline, comprising data acquisition, two-layer CNN training with Adam o

On Emergent Social World Models -- Evidence for Functional Integration of Theory of Mind and Pragmatic Reasoning in Language Models

arXiv:2602.10298v2 Announce Type: replace Abstract: This paper investigates whether LMs recruit shared computational mechanisms for general Theory of Mind (ToM) and language-specific pragmatic reasoni

researcharxiv-cs-cl

PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Sampling

arXiv:2410.05970v3 Announce Type: replace-cross Abstract: Multimodal document understanding is a challenging task to process and comprehend large amounts of textual and visual information. Recent adva

Perfecting Aircraft Maneuvers with Reinforcement Learning

arXiv:2604.24338v1 Announce Type: new Abstract: This paper evaluates an advanced jet trainer's utilization of artificial intelligence (AI)-based aircraft aerobatic maneuvers with the intention of deve

PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysis

arXiv:2512.22113v2 Announce Type: replace-cross Abstract: Unresolved production cloud incidents cost an average of over $2M per hour. This paper introduces PRAXIS, an orchestrator that manages and dep

Quasi-Quadratic Gradient: A New Direction for Accelerating the BFGS Method in Quasi-Newton Optimization

arXiv:2604.23922v1 Announce Type: cross Abstract: In this paper, we introduce the Quasi-Quadratic Gradient (QQG), a novel search direction designed to accelerate the BFGS method within the quasi-Newto

researcharxiv-cs-ai

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization

arXiv:2408.00923v2 Announce Type: replace-cross Abstract: This paper explores a novel paradigm in low-bit (i.e. 4-bits or lower) quantization, differing from existing state-of-the-art methods, by fram

Representation Homogeneity and Systemic Instability in AI-Dominated Financial Markets: A Structural Approach

arXiv:2604.22818v1 Announce Type: cross Abstract: This paper investigates how similarity in the informational representation of market states among Artificial Intelligence (AI) trading agents can gene

agentsarxiv-cs-ai