Search: “applications”

Quantifying the Gap Between Laboratory Battery Test Patterns and Field Duty Profiles

arXiv:2608.16212v1 Announce Type: new Abstract: Laboratory battery tests provide the main empirical basis for battery performance and degradation studies, but their operating patterns do not directly

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QUMem: Personalized Memory for Query-Conditioned User-State Inference in LLM Agents

DGX agent

arXiv:2608.16168v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly use external memory systems to support personalization by drawing on long and evolving interaction hist

researcharxiv-cs-ai

18 Aug 2026

Real-Time State-of-Health Estimation and Online Degradation Prognosis from Partial Battery Discharge Using Physics-Informed Neural Networks

arXiv:2608.14764v1 Announce Type: new Abstract: With the increasing integration of renewable energy sources, energy storage systems have become essential, making the accurate estimation of their State

Reasoning-supported Robustness Validation of Automotive E/E Components

arXiv:2608.16421v1 Announce Type: new Abstract: This paper presents an ontology-supported approach to tackle the complexity of the Robustness Validation (RV) process of automotive electrical/electroni

Tutorials

RetroMPA: A Molecular Property-Aware Auxiliary Framework for Enhancing Retrosynthesis Prediction

arXiv:2608.16111v1 Announce Type: cross Abstract: Retrosynthesis is a cornerstone of drug discovery and organic synthesis. While data-driven deep learning models have shown remarkable progress, they a

tutorialsarxiv-cs-ai

Agents

RingMo-Agent: A Unified Remote Sensing Foundation Model for Multi-Platform and Multi-Modal Reasoning

arXiv:2507.20776v3 Announce Type: replace Abstract: Remote sensing (RS) images from multiple modalities and platforms exhibit diverse details due to differences in sensor characteristics and imaging p

agentsarxiv-cs-cv

Agents

RoboStriker: Latent-Space Strategic Games for Autonomous Humanoid Boxing

arXiv:2608.16195v1 Announce Type: new Abstract: Achieving human-level competitive intelligence and physical agility in humanoid robots remains a profound challenge, particularly in contact-rich and hi

agentsarxiv-cs-ro

Sequential Batch Learning in Finite-Action Linear Contextual Bandits

arXiv:2004.06321v2 Announce Type: replace Abstract: We study the sequential batch learning problem in linear contextual bandits with finite action sets, where the decision maker is constrained to spli

safetyarxiv-cs-lg

Shape Operator PCA: Curvature-Aware Projections for Geometric Machine Learning

arXiv:2608.15313v1 Announce Type: cross Abstract: In this paper, we propose SHOPCA (Shape Operator-based Principal Component Analysis), a novel method for unsupervised metric learning and dimensionali

Skill2Query: Exploiting Skill Structure to Generate Pseudo-Queries for Agent Skill Retrieval

model-releasesarxiv-cs-cl

arXiv:2608.16071v1 Announce Type: new Abstract: Pseudo-query generation can alleviate the supervision bottleneck for agent skill retrieval, but existing document-level approaches typically leave the r

SOS! : A Streamlined Object-Conditional Transformer for Model-free Segmentation

arXiv:2608.15295v1 Announce Type: new Abstract: Foundation segmentation models excel at generating high-quality, class-agnostic masks, but they struggle to associate these proposals with specific targ

researcharxiv-cs-cv

Sterilizable Scene Graph Generation for Operating Rooms

model-releasesarxiv-cs-cv

arXiv:2608.16469v1 Announce Type: new Abstract: Scene graph generation from surgical video enables a holistic and structured understanding of surgical scenes by modeling objects and their semantic rel

Sufficient Dimesion Reduction via Generalized Stein's Lemma

arXiv:2608.15121v1 Announce Type: cross Abstract: Sufficient dimension reduction (SDR) seeks the minimal subspace of the predictors that captures the full conditional distribution of the response, whi

Synthetic Data Augmentation for Satellite-Based Analysis of Battle-Damaged Agricultural Fields in Ukraine

arXiv:2608.16380v1 Announce Type: cross Abstract: Monitoring war-induced damage to agricultural land in Ukraine is important for understanding threats to food security, environmental stability, and po

The canonical facets of multi-separator polytopes

arXiv:2608.16861v1 Announce Type: cross Abstract: We initiate a polyhedral study of the graph multi-separator problem proposed by Irmai et al. (2024) as an alternative to the lifted multicut problem f

The Fragility of Strategic Thinking in Large Language Models

arXiv:2510.10813v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly applied to domains that require reasoning about other agents' behavior, such as negotiation, policy de

safetyarxiv-cs-ai

Time-Correlated Video Bridge Matching

model-releasesarxiv-cs-lg

arXiv:2510.12453v3 Announce Type: replace Abstract: Diffusion models excel in noise-to-data generation tasks, providing a mapping from a Gaussian distribution to a more complex data distribution. Howe

TokenSTFormer: A Tokenized Spatial-temporal Attention Model for Holistic Motion Analysis in Adolescent Idiopathic Scoliosis Screening

arXiv:2608.16122v1 Announce Type: cross Abstract: Adolescent Idiopathic Scoliosis (AIS) is a prevalent spinal deformity in adolescents that, if left untreated, can result in severe health outcomes. Tr

Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey

arXiv:2510.10903v2 Announce Type: replace Abstract: Embodied intelligence has witnessed remarkable progress in recent years, driven by advances in computer vision, natural language processing, and the

safetyarxiv-cs-ro

Translating finite-domain integer constraint models to CP/SMT/ILP/PB/SAT solvers with CPMpy

arXiv:2608.15143v1 Announce Type: new Abstract: Constraint solving is a declarative approach for solving combinatorial satisfaction and optimization problems. The user specifies their problem through

UAV Video Deblurring via Motion-Aware Diffusion: A Path to Robust Target Detection

arXiv:2608.15259v1 Announce Type: cross Abstract: Unmanned Aerial Vehicles (UAVs) play a crucial role in various scenarios ranging from disaster response to traffic surveillance. However, aerial video

safetyarxiv-cs-ai

UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrations

arXiv:2608.15930v1 Announce Type: new Abstract: Foundation GUI agents can automate complex digital tasks, but deployment is hindered by scarce and biased training data, ambiguous prompts, and unreliab

UrbanWorld2.0: A Multimodal Agentic Framework for Reality-Aligned 3D World Generation at City-Scale

arXiv:2511.18005v2 Announce Type: replace Abstract: The automated generation of high-fidelity, city-scale 3D environments remains a formidable challenge with profound academic and industrial implicati

safetyarxiv-cs-cv

When AI Rewrites, Classifiers Relax: Uncertainty-Aware Sentiment Analysis on Sarcastic and AI-Paraphrased Social Text

arXiv:2608.15338v1 Announce Type: cross Abstract: Sentiment classifiers are increasingly applied to social media content that is either sarcastic or AI-generated --- two distributional regimes where s

safetyarxiv-cs-ai

When Entropy Is Not Enough: Reclaiming Lost Semantics in LLM Output Length Prediction

arXiv:2608.15592v1 Announce Type: new Abstract: Efficient LLM serving is often bottlenecked by the need to pad sequences to a fixed maximum length, and this wastes compute and degrades throughput. Pre

When Less Is Enough: Context Selection and Prompting Strategies for Bengali News Headline Generation

model-releasesarxiv-cs-cl

arXiv:2608.15879v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance in text generation tasks, yet their effectiveness on headline generation remains sensitive to

A Probabilistic Framework for Learnable Optimization Algorithms

arXiv:2408.11629v2 Announce Type: replace Abstract: We propose a statistical-learning framework for optimization algorithms. The framework is based on probability distributions over optimization traje

A Subjective Study on a New Sharpness Informed Class of Metrics

arXiv:2608.13989v1 Announce Type: cross Abstract: Perceptual loss functions in Deep Neural Network (DNN) deblurring architectures improve the overall quality of restored images. However, few focus on

researcharxiv-cs-cv

A Survey of Large Models in Sports

arXiv:2608.14377v1 Announce Type: new Abstract: Sports have witnessed growing global enthusiasm in recent years, serving as a vital force for physical health, cultural exchange, social connection, and

researcharxiv-cs-cl

Adversarial Learning of Classifier-Free Guidance Schedules

arXiv:2608.14038v1 Announce Type: new Abstract: Modern text-to-image diffusion models rely on classifier-free guidance (CFG) to achieve high image fidelity and text alignment. However, CFG typically a

safetyarxiv-cs-lg

After pushing 1M+ tokens through Qwen 3.8 27B, here is my optimal llama.cpp config for 16GB VRAM (73k Context, Agentic Coding)

model-releasesr-localllama

Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance.

AI-Assisted Discovery and Construction of a Counterexample to the Convergence of Three-Block ADMM with the Identity Matrix as its Third Constraint Block

arXiv:2608.14396v1 Announce Type: cross Abstract: The alternating direction method of multipliers (ADMM), as a landmark algorithm, has attracted tremendous research attention and extensive practical a

Automated Inference of Graph Transformation Rules

arXiv:2404.02692v3 Announce Type: replace-cross Abstract: The explosion of data available in life sciences is fueling an increasing demand for expressive models and computational methods. Graph transf

CFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models

arXiv:2607.14975v2 Announce Type: replace Abstract: Channel foundation models (CFMs) are commonly evaluated in model-specific pipelines that differ in data, radio configurations, partitions, adaptatio

Consensus-gated Multi-Agent Neural Architecture Search for Seismic Fault Segmentation

model-releasesarxiv-cs-cv

arXiv:2608.13889v1 Announce Type: new Abstract: Neural networks for seismic fault segmentation are often borrowed from computer vision and medical imaging domains where they train under relatively muc

Don't Claim Benchmark-Oriented Optimization Improves General Coding Capability -- Diverse Evaluation Is Required

arXiv:2608.13566v1 Announce Type: cross Abstract: Post-training papers, model cards, and blog posts often treat scores on a small set of coding benchmarks (e.g., SWE-bench and LiveCodeBench) as eviden

Local Ai

E-S2Feat:Semantic-Guided Spiking Local Feature Detection and Description for Event Cameras

arXiv:2608.14027v1 Announce Type: new Abstract: Benefiting from high temporal resolution and dynamic range, event-based local feature methods have attracted increasing attention. However, event sparsi

local-aiarxiv-cs-cv

Federated Prompt Learning: A Unified Framework, Empirical Analysis, and Future Directions

arXiv:2608.13844v1 Announce Type: cross Abstract: Large language models (LLMs) have become core components of cloud-based intelligent services in academia and industry, yet their training and deployme

FLARE MCMC: Fidelity-based Layer-Adaptive REcursive proposals for MCMC

arXiv:2608.13774v1 Announce Type: new Abstract: Markov chain Monte Carlo (MCMC) requires only the ability to evaluate the likelihood, making it a common technique for inference in complex models. Howe

From BERT to Frontier Agents: Eight Years of Language-Model Progress, the Collapse of the Capability-Cost Curve, and the Rise of Task-Targeted Models

arXiv:2608.13675v1 Announce Type: cross Abstract: Between October 2018 and July 2026 AI models progressed from simple systems like BERT to massive agents that solve complex math and write software. Th

Tutorials

Global Interpretability via Automated Preprocessing: A Framework Inspired by Psychiatric Questionnaires

arXiv:2602.23459v2 Announce Type: replace Abstract: Psychiatric questionnaires are highly context sensitive and often only weakly predict subsequent symptom severity, which makes the prognostic relati

tutorialsarxiv-cs-lg

Tutorials

Learning to Forecast Crop Growth from Earth Observation Data

arXiv:2608.14281v1 Announce Type: new Abstract: Forecasting crop growth across agricultural landscapes is important for improving the productivity, resilience, and operational management of farming sy

tutorialsarxiv-cs-cv

Learning Unsteady Aneurysm Hemodynamics with Physics-Informed DeepONets

arXiv:2608.13629v1 Announce Type: cross Abstract: Clinically actionable, patient-specific hemodynamic assessment, specifically wall shear stress, vortex structure and pressure distributions, is critic

LP-NAS: Linear Programming-based Neural Architecture Search

arXiv:2608.14472v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) aims to automate neural network architecture design, reducing reliance on human expertise. Among the various NAS meth

Model-agnostic Retrieval-Augmented Extended Forecasting for time series

model-releasesarxiv-cs-lg

arXiv:2608.14054v1 Announce Type: new Abstract: Time series forecasting with pretrained foundation models has demonstrated strong zero-shot capabilities. However, achieving optimal performance on time

Local Ai

Point-Cloud-Assistant Localized Statistical Channel Prediction by Tangent Gaussian Splatting

arXiv:2606.18734v2 Announce Type: replace-cross Abstract: Accurate, site-specific channel information is crucial for optimizing next-generation wireless networks. Among various approaches, localized s

local-aiarxiv-cs-lg

Agents

Polaris : Multi Agentic System for Conversational Enterprise Analytics

arXiv:2608.14246v1 Announce Type: new Abstract: In today's fast-paced environment, the ability to swiftly access, understand, and act on data is no longer optional; it is essential. Yet most organizat

agentsarxiv-cs-ai

Probabilistic indirect models for undrained shear strength: addressing significant data missing and variability with advanced imputation and machine learning techniques

arXiv:2608.13934v1 Announce Type: new Abstract: Accurate prediction of undrained shear strength (su) is crucial for geotechnical design, but is often hampered by substantial uncertainty in traditional