Search: “applications”

How to Achieve the Intended Aim of Deep Clustering Now, without Deep Learning

arXiv:2602.05749v2 Announce Type: replace Abstract: Deep clustering (DC) is often quoted to have a key advantage over k-means clustering. Yet, this advantage is often demonstrated using image datasets

tutorialsarxiv-cs-lg

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Image Difference Quantification Using Autoencoder-Based Latent Representations

DGX agent

arXiv:2608.24782v1 Announce Type: new Abstract: Traditional image similarity metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and the Structural Similarity Index Measure (S

researcharxiv-cs-cv

26 Aug 2026

It depends: Incorporating correlations for joint aleatoric and epistemic uncertainties of high-dimensional output spaces

arXiv:2608.24518v1 Announce Type: cross Abstract: Uncertainty Quantification (UQ) plays a vital role in enhancing the reliability of deep learning model predictions, especially in scenarios with high-

researcharxiv-cs-cv

Joint Distribution Alignment for Universal Domain Adaptation

arXiv:2608.24429v1 Announce Type: cross Abstract: Unsupervised domain adaptation (UDA) has been widely concerned in the fields of machine learning, pattern recognition, and computer vision. Traditiona

safetyarxiv-cs-cv

Learning to Grade Efficiently: A Bandit-Driven Prompt-Selection Framework for Low-Cost LLM Essay Scoring

arXiv:2608.23814v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate strong capabilities in automated essay scoring (AES), but contemporary approaches typically employ fixed prom

Lifted Model Construction under Approximate Commutativity

arXiv:2608.24713v1 Announce Type: new Abstract: Lifted inference algorithms enable scalable probabilistic inference even for large object domains by leveraging the indistinguishability of objects in a

LLM Agents Perform Controlled Experiments Using Simulation Models

arXiv:2608.23622v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong capabilities in reasoning, planning, and tool use, but many scientific and engineering tasks require more

MolGA: Molecular Graph Adaptation with Pre-trained 2D Graph Encoder

arXiv:2510.07289v2 Announce Type: replace Abstract: Molecular graph representation learning is widely used in chemical and biomedical research. While pre-trained 2D graph encoders have demonstrated st

safetyarxiv-cs-lg

Phase-Aligned Finite-Fourier Periodic Deformation for 4D Medical Image Interpolation

arXiv:2608.24027v1 Announce Type: new Abstract: 4D medical image interpolation aims to recover missing volumes from sparsely observed time points and is important for dynamic anatomical analysis in ap

researcharxiv-cs-cv

Predictability of El Nino from Delayed Observations

arXiv:2608.24428v1 Announce Type: cross Abstract: Using monthly Nino-3.4 anomalies through July 2026, we investigate how much predictive information is contained in delayed observations of the index.

Quantum Maximum Entropy Inference and Hamiltonian Learning

arXiv:2407.11473v2 Announce Type: replace Abstract: Maximum entropy inference and learning of graphical models are pivotal tasks in learning theory and optimization. This work extends algorithms for t

RePolicy: Reinforcement Learning for Safety-Policy Invocation in Agent Safeguards

arXiv:2608.24275v1 Announce Type: new Abstract: Safeguarding language model agents requires assessing complete execution trajectories under context-dependent safety policies. Existing policy-aware saf

S-matrix informed neural networks for amplitude analysis

arXiv:2608.23750v1 Announce Type: cross Abstract: Reconstructing scattering amplitudes from finite, noisy, and mutually inconsistent measurements is an ill-posed inverse problem common to many reactio

tutorialsarxiv-cs-lg

TLXML: Task-Level Explanation of Meta-Learning via Influence Functions

arXiv:2501.14271v4 Announce Type: replace Abstract: Meta-learning enables models to rapidly adapt to new tasks by leveraging prior experience, but its adaptation mechanisms remain opaque, especially r

Validation of HRV Studio: A Transparent and Quality-Control-Aware Platform for Heart Rate Variability Analysis

arXiv:2608.24241v1 Announce Type: cross Abstract: Reproducibility of heart rate variability (HRV) analysis is limited by differences in preprocessing and computational conventions across software plat

A Data-Driven Approach to State Construction in Markov Models

arXiv:2608.21480v1 Announce Type: cross Abstract: A Markov chain is a widely used stochastic process modelling random events over time. These models are built on subsets of the entire dataset, referre

A Scalable Cross-Domain Event Extraction System via a Unified Generative Training Framework

arXiv:2608.23261v1 Announce Type: new Abstract: Event extraction is fundamental to information extraction. Prior approaches often separate event detection and argument extraction or depend on dataset-

researcharxiv-cs-cl

A Survey on Human-AI Collaboration with Large Foundation Models

arXiv:2403.04931v4 Announce Type: replace Abstract: As the capabilities of artificial intelligence (AI) continue to expand rapidly, Human-AI (HAI) Collaboration, combining human intellect and AI syste

AI Surrogate Modeling for Real-Time Tokamak Equilibrium Prediction: Benchmarking Neural Architectures and Validation on EXL-50U

arXiv:2608.23217v1 Announce Type: cross Abstract: Fast and reliable plasma equilibrium prediction is essential for real-time tokamak operation and control, but conventional Grad-Shafranov (GS) solvers

AI University: An LLM-Powered Learning Assistant for Engineering---A Finite Element Method Case Study

arXiv:2504.08846v2 Announce Type: replace-cross Abstract: We introduce AI University (AI-U), a flexible framework for AI-driven course content delivery that adapts to a course's instructional style. A

Local Ai

Barycentric Fused Gromov-Wasserstein Balancing for Causal Inference under Multiple Treatments

arXiv:2608.22024v1 Announce Type: cross Abstract: Estimating heterogeneous single and interaction treatment effects from observational data under multiple simultaneous treatments is crucial for decisi

local-aiarxiv-cs-ai

Beyond What Meets the Eye: Unveiling Situational Illusions for Multimodal Large Language Models

arXiv:2608.22232v1 Announce Type: new Abstract: Real-world situation appearances can deviate from their underlying physical states, challenging the reliability of multimodal large language models (MLL

Hardware

BIMScript: Material-Aware Structured Scene Programs for BIM Ingestion

arXiv:2608.21447v1 Announce Type: new Abstract: Structured-language models such as SceneScript reconstruct a scene as a short program of parametric commands, an inherently editable and semantically ex

hardwarearxiv-cs-cv

BLADE: Bilevel Low-rank Augmented-Lagrangian Erasure for LLM Unlearning

arXiv:2608.22557v1 Announce Type: cross Abstract: Existing LLM unlearning methods struggle with robustness: unbounded forget losses degrade model coherence, fixed-weight balancing cannot adapt as reta

ByteAction: Byte-space Action Recognition Foundation Model

arXiv:2608.22760v1 Announce Type: new Abstract: Byte-space Action Recognition (BAR) aims to recognize human actions directly from compressed image bitstreams without any pixel decoding. By operating e

tutorialsarxiv-cs-cv

CausalCache: Conditional High-Fidelity Restoration for Long-Horizon GUI Agents

arXiv:2608.22577v1 Announce Type: new Abstract: Long-horizon GUI agents can retain a complete interaction trace cheaply as textual action records, but expose only a few past events to the policy in hi

ChebBooster: A Training-Free Approach for Efficient Diffusion Transformer Inference via Chebyshev-Inspired Extrapolation

arXiv:2608.23429v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) have shown strong performance in high-fidelity image generation, but their sampling process remains computationally inte

ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language model

arXiv:2504.09421v3 Announce Type: replace-cross Abstract: Recent advances in reasoning with large language models (LLMs)has shown remarkable reasoning capabilities in domains such as mathematics and c

Cognitive Profiling of LRMs' Reasoning Traces Using Bloom's Taxonomy

arXiv:2608.23205v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have revolutionized reasoning in LLMs, and the increasing public availability of reasoning traces creates valuable opportu

Continual Uncertainty Learning for Robust Control of Nonlinear Systems with Multiple Heterogeneous Uncertainties

arXiv:2602.17174v3 Announce Type: replace-cross Abstract: Robust control of mechanical systems with multiple uncertainties remains a fundamental challenge, particularly when nonlinear dynamics and ope

ConvergeWriter: Data-Driven Bottom-Up Article Construction

model-releasesarxiv-cs-cl

arXiv:2509.12811v2 Announce Type: replace Abstract: Large Language Models (LLMs) have shown remarkable prowess in text generation, yet producing long-form, factual documents grounded in extensive exte

Cross-Subject Generalization in Decoding Perceived Speech from Non-Invasive Brain Recordings

arXiv:2608.22420v1 Announce Type: cross Abstract: Decoding perceived speech from non-invasive brain recordings has garnered significant attention in recent years due to its wide range of potential app

Cross-validating causal discovery via Leave-One-Variable-Out

arXiv:2411.05625v2 Announce Type: replace-cross Abstract: We propose a new approach to falsify causal discovery algorithms without ground truth, which is based on testing the causal model on a variabl

Development and Feasibility Evaluation of an Edge AI as Medical Device System for Breast Cancer Multidisciplinary Team Meetings

arXiv:2608.22108v1 Announce Type: new Abstract: Breast Cancer Multidisciplinary Team (MDT) meetings manage increasingly complex cases under considerable time pressure, and documentation requirements c

Exploring Dowker Homology for Sentence Similarity

arXiv:2608.22909v1 Announce Type: new Abstract: Dowker homology is a topological tool that may be used to analyze the relative position of two point clouds living in a common space. We investigate whe

researcharxiv-cs-cl

From Symmetry to Invariance: Learning Galois Equivalent Representations in Finite Fields

arXiv:2608.22513v1 Announce Type: new Abstract: Neural networks can learn algebraic operations from finite examples, but it remains unclear whether this ability transfers across mathematically equival

tutorialsarxiv-cs-lg

Gate Voltage Effect on Pulse Detection Efficiency of Perimeter-Gated SPADs

arXiv:2608.21371v1 Announce Type: cross Abstract: Perimeter-gated single-photon avalanche diodes (pg-SPADs) are known for their dynamic dark noise modulation capabilities. They are reported to trade n

researcharxiv-cs-cv

GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answering

arXiv:2608.22634v1 Announce Type: cross Abstract: Current work on improving reliability in large language model (LLM)- generated answers has primarily leveraged Retrieval-Augmented Generation (RAG), k

Graph Representation Learning of Lightweight IoT Ciphers

arXiv:2608.23054v1 Announce Type: new Abstract: SIMON and SIMECK belong to a family of Lightweight Cryptographic Algorithms (LCAs) based on the Feistel block cipher, designed for Internet of Things (I

K-Bench: measuring model performance on real scientific agent requests

arXiv:2608.21601v1 Announce Type: new Abstract: Benchmarks for scientific artificial intelligence are mostly written to be scored: multiple-choice questions, curated agent tasks with reference solutio

LagrangeGS: Non-Conservative Lagrangian System on Dynamic 3D Gaussian Splatting

arXiv:2608.22773v1 Announce Type: new Abstract: Dynamic 3D Gaussian Splatting (3DGS) achieves photorealistic reconstruction of time-varying scenes, and recent physics-aware extensions improve extrapol

safetyarxiv-cs-cv

Learning from the Test: Self-Referential Differential Testing for Deep RL Agents

arXiv:2608.22284v1 Announce Type: cross Abstract: Deep Reinforcement Learning (DRL) has achieved significant success in complex decision-making problems. As DRL systems are increasingly deployed in re

Learning Reduced-Order Dynamics with Singularity via Latent-Augmented Neural Ordinary Differential Equations

arXiv:2608.22142v1 Announce Type: new Abstract: This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented

Learning with Local Search MCMC Layers

arXiv:2505.14240v3 Announce Type: replace Abstract: Integrating combinatorial optimization layers into neural networks has recently attracted significant research interest. However, many existing appr

Agents

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM

arXiv:2509.20067v5 Announce Type: replace Abstract: Large language models (LLMs) have shown promise in supporting medical diagnosis, with prompting-based methods offering a flexible and deployable mea

agentsarxiv-cs-ai

Local Ai

Minimal Local Simulation Foundations for LLM- and VLM-Driven Agents in 2D and 3D Environments

arXiv:2608.22833v1 Announce Type: cross Abstract: Large language models (LLMs) and vision-language models (VLMs) are expanding the range of behaviors that can be represented in agent-based simulations

local-aiarxiv-cs-ai

Agents

MIVIFI: Bridging Perspective and Fisheye Domains for Training Multi-View Fisheye Image Generation Models

arXiv:2608.23140v1 Announce Type: new Abstract: Achieving 360{eg} coverage is critical for the visual perception systems of autonomous vehicles. Fisheye cameras offer a cost-effective solution by enab

agentsarxiv-cs-cv

MobilePA-Bench: Benchmarking Mobile Planner Agents on Complex Real-World Tasks

arXiv:2608.23035v1 Announce Type: new Abstract: As on-device LLM agents evolve into personal copilots, the mobile operating system has become a key testbed for this paradigm, making rigorous capabilit