Search: “applications”

Neural ensemble Kalman filter: Data assimilation for compressible flows with shocks

arXiv:2602.23461v2 Announce Type: replace-cross Abstract: Data assimilation (DA) for compressible flows with shocks is challenging because many classical DA methods generate spurious oscillations and

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Research

Neuron-based Personality Trait Induction in Large Language Models

DGX agent

arXiv:2410.12327v2 Announce Type: replace Abstract: Large language models (LLMs) have become increasingly proficient at simulating various personality traits, an important capability for supporting re

researcharxiv-cs-cl

11 Jun 2026

Reinforcement Learning with Action-Triggered Observations

arXiv:2510.02149v2 Announce Type: replace Abstract: We introduce Action-Triggered Sporadically Traceable Markov Decision Processes (ATST-MDPs), a reinforcement learning framework for partial observabi

safetyarxiv-cs-lg

Renewable Lasso without Batch-Number Constraints: A Gradient-Enhanced Approach

arXiv:2606.11738v1 Announce Type: cross Abstract: We study online estimation for high-dimensional generalized linear models with streaming data. First, for the non-distributed setting, we propose a gr

Scene-Adaptive Nonlinear Tone Curves for Pseudo Ground-Truth Generation in Low-Light 3D Gaussian Splatting

arXiv:2606.11841v1 Announce Type: new Abstract: Low-light novel view synthesis is challenging because dark multi-view images contain noise, weak structural detail, and compressed dynamic range. Recent

Local Ai

Seeing What Matters: Perceptual Wrapper with Common Randomness for 3D Gaussian Splatting

arXiv:2606.11782v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) achieves impressive real-time rendering, it frequently struggles to synthesize high-frequency textures, a limitation

local-aiarxiv-cs-cv

SoftMatcha 2: A Fast and Soft Pattern Matcher for Trillion-Scale Corpora

model-releasesarxiv-cs-cl

arXiv:2602.10908v2 Announce Type: replace Abstract: We present SoftMatcha 2, an ultra-fast and flexible search algorithm that enables search over trillion-scale natural language corpora in under 0.3 s

SPADE: Split-and-Delay Embeddings for Autoregressive High-Granularity Calorimeter Simulation

arXiv:2606.11304v1 Announce Type: cross Abstract: We introduce SPADE (SPlit And Delay Embeddings), an autoregressive transformer for sequences whose tokens carry multiple features. Rather than embeddi

TaskFusion: Continual Anomaly Detection for Heterogeneous Tabular Data

arXiv:2606.11844v1 Announce Type: new Abstract: Continual anomaly detection in tabular data is challenging and remains largely underexplored, particularly in settings with heterogeneous feature schema

tutorialsarxiv-cs-lg

Local Ai

Tree-Structured Orthonormal Decomposition of the Aitchison Simplex

arXiv:2606.11646v1 Announce Type: new Abstract: Compositional data -- vectors encoding relative proportions -- arise across scientific domains, including ecology, geochemistry, and genomics. The featu

local-aiarxiv-cs-lg

Urban Heat MiniCubes: An AI-Ready dataset for urban heat research

arXiv:2606.11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify becau

safetyarxiv-cs-lg

Weighted Random Dot Product Graphs

arXiv:2505.03649v4 Announce Type: replace-cross Abstract: Modeling of intricate relational patterns has become a cornerstone of contemporary statistical research and related data science fields. Netwo

A Large Scale Open-Source Image and Video Dataset for Robust Wildfire Detection and Classification

model-releasesarxiv-cs-cv

arXiv:2606.10174v1 Announce Type: new Abstract: Wildfire detection and monitoring are critical for mitigating fire spread and reducing environmental and infrastructural damage. In this work, we introd

A Unified Multi-Modal Framework for Intelligent Financial Systems: Integrating Reinforcement Learning, High-Frequency Trading, and Game-Theoretic Approaches with Cross-Modal Sentiment Analysis

arXiv:2606.10412v1 Announce Type: new Abstract: The rapid evolution of financial technology demands sophisticated artificial intelligence systems capable of handling diverse challenges across multiple

safetyarxiv-cs-ai

Alignment Defends LLMs from Property Inference Attacks

arXiv:2606.10217v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly fine-tuned on domain-specific datasets that may contain sensitive, dataset-level properties. Recent work h

safetyarxiv-cs-lg

Automated Scoring of Arabic Text Using Large Language Models: A Literature Review

arXiv:2606.09830v1 Announce Type: new Abstract: In modern educational systems, Automatic Text Scoring (ATS) plays a central role by enabling scalable and consistent evaluation of learner responses wit

safetyarxiv-cs-cl

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective

arXiv:2502.01272v3 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have achieved notable success in tasks such as social and transportation networks. However, recent studies have highlig

ClusBench: The Clustering Benchmark Data Resource You've All Been Waiting For (?)

arXiv:2606.10673v1 Announce Type: cross Abstract: Although some very common test beds exist for assessing the performance of clustering methods, large scale benchmarking is typically limited to relati

CoCoSI: Collaborative Cognitive Map Construction for Spatial Intelligence

model-releasesarxiv-cs-cv

arXiv:2606.10401v1 Announce Type: new Abstract: Spatial intelligence is a key frontier for multimodal large language models (MLLMs), enabling them to reason about the physical world from visual experi

Local Ai

COGENT: Continuous Graph Emulators with Neural Ordinary Differential Equations for Long-Term Physical Forecasting

arXiv:2606.11162v1 Announce Type: new Abstract: In this work, we present COGENT, a continuous graph emulator with Neural Ordinary Differential Equations for long-term physical forecasting on irregular

local-aiarxiv-cs-lg

Content-Induced Spatial-Spectral Aggregation Network for Change Detection in Remote Sensing Images

arXiv:2606.10328v1 Announce Type: cross Abstract: The integration of spatial and spectral information is beneficial to the improvement of change detection performance. However, existing methods cannot

tutorialsarxiv-cs-ai

Efficient AI-Inspired Reduction of Feynman Integrals via Tube Seeding

arXiv:2606.10698v1 Announce Type: cross Abstract: In this paper, we use machine learning to discover a new seeding strategy for integration-by-parts reduction of Feynman integrals, which is a frequent

Entropy, Disagreement, and the Limits of Foundation Models in Genomics

arXiv:2604.04287v2 Announce Type: replace-cross Abstract: Foundation models in genomics have shown mixed success compared to their counterparts in natural language processing. Yet, the reasons for the

tutorialsarxiv-cs-cl

Equanimity in HRI: Applying Calm Technology Principles to Human-Robot Interaction

arXiv:2606.09836v1 Announce Type: cross Abstract: This paper explores how {extit{Calm Technology}} can be integrated into Human-Robot Interaction (HRI), with a particular focus on the household enviro

researcharxiv-cs-ro

Fisher-Guided Progressive Parameter Selection for Adaptive Fine-Tuning

model-releasesarxiv-cs-ai

arXiv:2606.10196v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) aims to adapt pretrained models with a small trainable parameter subset, however, most existing methods choose

From Data Heterogeneity to Convergence: A Data-Centric Review of Federated Learning

arXiv:2606.10595v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising solution for data hunger in centralized learning. This paradigm enables privacy with multiple clien

FSS-Net: Frequency-Spatial Synergy Network with Wavelet Attention for Carotid Artery Ultrasound Segmentation

arXiv:2606.10378v1 Announce Type: new Abstract: Accurate segmentation of carotid arteries in ultrasound imaging is critical for stroke risk assessment. However, speckle noise, low contrast, and blurre

GAGI: A Gini-Adjusted GDP-per-Capita Index for Distribution-Aware Macroeconomic Welfare Monitoring

arXiv:2606.09944v1 Announce Type: cross Abstract: GDP per capita is the default lens through which governibng bodies track the economic prosperity and consequences of economic events , yet it is blind

Geometric Formulation of Unified Force-Impedance Control on SE(3) for Robotic Manipulators

arXiv:2504.17080v3 Announce Type: replace Abstract: In this paper, we present an impedance control framework on the SE(3) manifold, which enables force tracking while guaranteeing passivity. Building

researcharxiv-cs-ro

Glove2Hand: Synthesizing Natural Hand-Object Interaction from Multi-Modal Sensing Gloves

arXiv:2603.20850v2 Announce Type: replace Abstract: Understanding hand-object interaction (HOI) is fundamental to computer vision, robotics, and AR/VR. However, conventional hand videos often lack ess

GRAR: Glass-induced Reflection Artifact Removal in LiDAR Point Clouds

arXiv:2606.10541v1 Announce Type: new Abstract: Terrestrial Laser Scanning (TLS) point clouds captured in urban environments frequently suffer from glass-induced reflection artifacts, severely degradi

HiGR: Industrial-Scale Hierarchical Generative Slate Recommendation Framework in Tencent

arXiv:2512.24787v3 Announce Type: replace-cross Abstract: Slate recommendation, which presents users with a ranked item list in a single display, is ubiquitous across mainstream online platforms. Whil

safetyarxiv-cs-ai

Human-AI Coordination Zones: A Framework for Designing Human-in-the-Loop Experiences with Agentic AI

arXiv:2606.09848v1 Announce Type: cross Abstract: As generative and agentic AI becomes embedded in everyday products, practitioners face a persistent challenge: how to design human-AI coordination --

safetyarxiv-cs-ai

Integrated Real-Time Motion Tracking and AI Analysis for Athletic Performance Optimization

arXiv:2606.09842v1 Announce Type: cross Abstract: Applying Human Pose Estimation (HPE) in real world environments remains a challenging task, this paper explores and surveys real time HPE approaches a

tutorialsarxiv-cs-ai

Interactions Between Crosscoder Features: A Compact Proofs Perspective

arXiv:2606.09940v1 Announce Type: cross Abstract: Dictionary learning methods like Sparse Autoencoders (SAEs) and crosscoders attempt to explain a model by decomposing its activations into independent

Kwai Keye-VL-2.0 Technical Report

model-releasesarxiv-cs-cv

arXiv:2606.10651v1 Announce Type: new Abstract: We introduce Kwai Keye-VL-2.0-30B-A3B, an open-source Mixture-of-Experts (MoE) multimodal foundation model designed to advance long-video understanding

Magnetic HIP-NN for spin dynamics in disordered itinerant magnets

arXiv:2606.10349v1 Announce Type: cross Abstract: We present a magnetic extension of the Hierarchically Interacting Particle Neural Network (HIP-NN) that enables large-scale simulations of electron-me

Mean Flow Distillation: Robust and Stable Distillation for Flow Matching Models

arXiv:2606.11155v1 Announce Type: new Abstract: Flow Matching models have demonstrated strong performance across a wide range of generative tasks. However, their reliance on ODE-based iterative sampli

safetyarxiv-cs-cv

Mind the Gap: Can Frontier LLMs Pass a Standardized Office Proficiency Exam?

model-releasesarxiv-cs-ai

arXiv:2606.10956v1 Announce Type: new Abstract: The deployment of Large Language Model (LLM) agents for computer automation is accelerating, yet their ability to navigate complex, professional-grade p

NuWa: Deriving Lightweight Class-Specific Vision Transformers for Edge Devices

arXiv:2504.03118v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) often need to be compressed for deployment on resource-constrained edge devices like drones and smart vehicles. How

On the Condition Number Dependency in Bilevel Optimization

arXiv:2511.22331v2 Announce Type: replace-cross Abstract: Bilevel optimization minimizes an objective function, defined by an upper-level problem whose feasible region is the solution of a lower-level

One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data

arXiv:2606.10678v1 Announce Type: new Abstract: Transformer-based models have emerged as leading paradigms in time-series forecasting in recent years, employing self-attention mechanisms to capture lo

One Token per Multimodal Evidence: Latent Memory for Resource-Constrained QA

arXiv:2606.10572v1 Announce Type: new Abstract: External memory effectively grounds large language models (LLMs) and vision-language models (VLMs)-based question answering (QA) in relevant multimodal

Agents

Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey

arXiv:2403.00420v3 Announce Type: replace-cross Abstract: Deep Reinforcement Learning (DRL) is a subfield of machine learning for training autonomous agents that take sequential actions across complex

agentsarxiv-cs-ai

SARM2: Multi-Task Stage Aware Reward Modeling for Self Improving Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.10305v1 Announce Type: new Abstract: Fine-tuning vision-language-action (VLA) policies for long-horizon manipulation still relies heavily on behavior cloning, which requires costly high-qua

Spatiotemporal Graph Transformer for 3D Neighborhood Interaction and Quality Prediction in Metal Additive Manufacturing

arXiv:2606.10227v1 Announce Type: new Abstract: Metal additive manufacturing enables the fabrication of complex parts, but achieving consistent build quality remains challenging due to interactions in

tutorialsarxiv-cs-lg

Agents

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation

arXiv:2606.10749v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly moving from conversational interfaces to software components that plan, invoke tools, maintain memory, a

agentsarxiv-cs-ai

Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows

arXiv:2606.09857v1 Announce Type: new Abstract: Reduced-order models (ROMs) provide an efficient surrogate for complex multiscale systems, but their predictive accuracy is often compromised by truncat