Search: “framework”

arXiv:2603.24925v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) systems that rely on semantic search often fail to retrieve the complete set of evidence for complex queries, p

agentsarxiv-cs-lg

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Guided Discovery of New Behaviors using Diffusion Policies

DGX agent

arXiv:2606.08743v1 Announce Type: new Abstract: Diffusion models have become a powerful tool for generative modeling in robotics, with diffusion policies excelling at modeling multimodal action-trajec

safetyarxiv-cs-ro

9 Jun 2026

Hierarchical Projection for Adaptive Knowledge Transfer

arXiv:2606.08691v1 Announce Type: new Abstract: Modern data-driven applications increasingly involve learning from multiple heterogeneous sources, where a target dataset is limited but related informa

HiMat: DiT-based Ultra-High Resolution SVBRDF Generation

arXiv:2508.07011v5 Announce Type: replace Abstract: Creating ultra-high-resolution spatially varying bidirectional reflectance functions (SVBRDFs) is critical for photorealistic 3D content creation, t

safetyarxiv-cs-cv

Human-Centered Benchmarking of Driver Monitoring Models

arXiv:2606.08123v1 Announce Type: cross Abstract: Vision-based driver monitoring systems are increasingly deployed in safety-critical intelligent transportation settings, yet they are almost always co

Illumination-Invariant Anomaly Detection for Sub-Canopy UAV Multispectral Point Clouds

arXiv:2606.09111v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) multispectral point clouds (MPC) provide high-dimensional spatial-spectral data for sub-canopy target detection; however,

Improving User Experience with Personalized Review Ranking and Summarization

arXiv:2601.05261v2 Announce Type: replace-cross Abstract: Online consumer reviews are important decision-support resources in e-commerce, yet the increasing volume of reviews often creates information

INFUSER: Influence-Guided Self-Evolution Improves Reasoning

arXiv:2606.09052v1 Announce Type: cross Abstract: Self-evolution offers a scalable path to stronger reasoning: a pretrained language model improves itself with only minimal external supervision. Yet e

Intention Driven Identification of In-Possession Match Phases in Association Football through Temporal Graph Learning

arXiv:2606.09289v1 Announce Type: new Abstract: Understanding tactical organisation of association football, hereafter referred to as football, requires identifying distinct match phases. Yet in-posse

LargeMonitor: Monitoring Online Task-Free Continual Learning via Large Pretrained Models

arXiv:2606.09430v1 Announce Type: cross Abstract: Online task-free continual learning (TFCL) requires intelligent agents to sequentially accumulate knowledge from an unbounded, non-stationary data str

Learning Predictive Control with Deep Koopman Operators for Autonomous Vehicle Motion Planning

model-releasesarxiv-cs-ro

arXiv:2606.08136v1 Announce Type: new Abstract: Model Predictive Control (MPC) is widely used for autonomous-vehicle (AV) motion planning, but its real-time applicability is often limited by the need

LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines

arXiv:2606.09489v1 Announce Type: new Abstract: Objective: Conformance checking in healthcare seeks to assess whether patient care pathways adhere to clinical guidelines. However, its practical applic

applicationsarxiv-cs-ai

MS-COOT: Comparing Morse-Smale Complexes with Co-Optimal Transport

arXiv:2606.08258v1 Announce Type: cross Abstract: Understanding and comparing structures in scalar fields is a central challenge in scientific visualization, with applications ranging from feature ana

Multimodal Group Emotion Recognition In-the-Wild Towards a Privacy-Safe Non-Individual Approach

arXiv:2606.07585v1 Announce Type: cross Abstract: This thesis addresses group emotion recognition (GER) in-the-wild with a focus on privacy preservation. Unlike traditional emotion recognition methods

applicationsarxiv-cs-ai

Neuro-Symbolic Injection of LTLf Constraints in Autoregressive Reinforcement Learning Policies

arXiv:2606.08312v1 Announce Type: new Abstract: In this work we study offline reinforcement learning (RL) under temporally extended task constraints expressed in Linear Temporal Logic over finite trac

Nonparametric LLM Evaluation from Preference Data

arXiv:2601.21816v2 Announce Type: replace Abstract: Evaluating the performance of large language models (LLMs) from human preference data is crucial for obtaining LLM leaderboards. However, many exist

applicationsarxiv-cs-lg

On the Complexity of Offline Reinforcement Learning with Q^star-Approximation and Partial Coverage

arXiv:2602.12107v2 Announce Type: replace-cross Abstract: We study offline reinforcement learning under Q^star-approximation and partial coverage, a setting that motivates practical algorithms such as

OnlyDense: Reduced-Order Modeling for Lagrangian simulation

arXiv:2606.09065v1 Announce Type: cross Abstract: In science and engineering, Lagrangian simulation methods such as Smooth Particle Hydrodynamics (SPH) or Material Point Method (MPM) are often employe

Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models

arXiv:2602.16061v2 Announce Type: replace-cross Abstract: Estimating population quantities such as mean outcomes from user feedback is fundamental to platform evaluation and social science, yet feedba

Partially Performative Prediction

arXiv:2606.07890v1 Announce Type: new Abstract: Performative prediction studies feedback loops that arise when predictive models are deployed in consequential domains. In these settings, deploying a m

Petri Net Modeling and Deadlock-Free Scheduling of Attachable Heterogeneous AGV Systems

arXiv:2508.00724v2 Announce Type: replace-cross Abstract: The increasing demand for flexible automation has accelerated the adoption of heterogeneous automated guided vehicles (AGVs). This work invest

safetyarxiv-cs-ro

Position: Genomic Model Research Must Move Beyond Anecdotal Evaluation of Interpretability Methods

arXiv:2606.07607v1 Announce Type: new Abstract: Advances in machine learning and computational power have unlocked the predictive potential of the human genome, yet biologists now demand that these mo

QnRL: Quantum-Native Reinforcement Learning

arXiv:2606.08276v1 Announce Type: cross Abstract: Quantum reinforcement learning (QRL) is a promising approach to learn effective decision strategies across several applications with stochastic enviro

Real-Time Industrial Defect Detection on Edge Hardware Using Fine-Tuned YOLOv8: A Systematic Benchmark on the NEU Surface Defect Database and MVTec AD with Automotive & Battery Manufacturing Extensions

model-releasesarxiv-cs-cv

arXiv:2606.07659v1 Announce Type: new Abstract: Automated surface defect detection is critical for ensuring rigorous quality control in high-speed manufacturing environments. While deep learning model

SAILS: Surrogate-based Analysis of Interactions via Local Effect Smooths

arXiv:2606.09404v1 Announce Type: cross Abstract: Feature interactions drive much of the predictive power of machine learning models, yet existing explanation methods only detect and quantify interact

local-aiarxiv-cs-ai

Scaling Decision-Focused Learning to Large Problems with Lagrangian Decomposition

arXiv:2606.08797v1 Announce Type: cross Abstract: Decision-focused learning has shown great promise for addressing predict-then-optimize problems, particularly in the presence of under-specified model

scCBGM: Interpretable Single-Cell Counterfactual Editing

model-releasesarxiv-cs-lg

arXiv:2606.07760v1 Announce Type: new Abstract: Understanding cellular phenotypes and how they respond to perturbations is critical for disease biology and therapeutic design. Single-cell RNA sequenci

SciTrace: Trajectory-Aware Safety Reasoning for Scientific Discovery Agents

arXiv:2606.08234v1 Announce Type: new Abstract: LLM-based scientific agents have shown strong capacity for autonomous research, yet their safety layers remain structurally divorced from core reasoning

Self-Consistent Generative Paths via Admissible Random Variational Transport

arXiv:2606.08953v1 Announce Type: new Abstract: Modern generative models often define an entire probability path from a simple prior to the data law, rather than only an endpoint map. Diffusion models

Self-Supervised Dynamical System Representations for Physiological Time-Series

arXiv:2512.00239v2 Announce Type: replace Abstract: The effectiveness of self-supervised learning (SSL) for physiological time series depends on the ability of a pretraining objective to preserve info

applicationsarxiv-cs-lg

Self-Supervised Learning with a Multi-Task Latent Space Objective

arXiv:2602.05845v2 Announce Type: replace Abstract: We propose a multi-task formulation of self-predictive Siamese SSL in which each spatial transformation defines a distinct latent-space alignment ta

safetyarxiv-cs-cv

Signals Are Not States: Neuro-Symbolic Safeguards for Culturally Aware Classroom AI

arXiv:2603.22793v2 Announce Type: replace Abstract: Classroom AI systems increasingly infer high-level educational states such as engagement, confusion, collaboration, participation, and instructional

SLMJury: Can Small Language Models Judge as Well as Large Ones?

arXiv:2606.07810v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used as judges for evaluating model outputs, but their high cost, latency, and opacity limit scalability. We i

Spectral Truncation Kernels: Noncommutativity in C^*-algebraic Kernel Machines

arXiv:2405.17823v5 Announce Type: replace-cross Abstract: A central question in vector- and function-valued learning is how to design kernels that capture both local and non-local interactions while r

SPIN: Decentralized Swarm Control via Tensorized Policy Coordination

arXiv:2606.07557v1 Announce Type: new Abstract: Decentralized multi-agent swarm coordination on resource-constrained edge platforms remains fundamentally bottlenecked by the exponential scaling of joi

Stain-Aware Wavelet Regularization for Instant Adversarial Purification in Histopathology

arXiv:2606.08745v1 Announce Type: new Abstract: Deep learning has become prevalent in computational pathology pipelines that support tasks such as cancer screening and digital pathology analysis. Howe

safetyarxiv-cs-cv

Tutorials

Statistical Decision Theory with Counterfactual Loss

arXiv:2505.08908v3 Announce Type: replace-cross Abstract: Many researchers apply classical statistical decision theory to evaluate treatment choices and learn optimal policies. However, because this f

tutorialsarxiv-cs-lg

STELLAR: Spatio-Temporal Environmental Learning with Latent Alignment and Refinement for Long-Tailed Species Distribution Modeling

arXiv:2606.08484v1 Announce Type: cross Abstract: Joint Species Distribution Modeling (JSDM) is a key enabler for biodiversity monitoring and conservation planning. However, accurate JSDM faces two co

Structural Decoupling: A Scaffold-Flow Theory of Generalization and Alignment

arXiv:2506.20699v2 Announce Type: replace Abstract: Learning in non-stationary and multi-context environments requires more than ordinary within-task generalization. A system must also discover which

Structured Neuron Pruning in Deep Neural Networks Using Multi-Armed Bandits

arXiv:2606.07615v1 Announce Type: cross Abstract: Deep neural networks often contain redundant hidden units. Removing individual weights can reduce parameter count, but unstructured sparsity is not al

Test-Time Adaptive Composition for Machine Learning as a Service (MLaaS) in IoT Environments

arXiv:2606.07685v1 Announce Type: cross Abstract: The dynamic nature of Internet of Things (IoT) environments affects the long-term effectiveness of Machine Learning as a Service (MLaaS) compositions.

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning

arXiv:2606.08231v1 Announce Type: new Abstract: Test-time Scaling (TTS) has emerged as a pivotal research direction for enhancing model performance by dynamically allocating computational resources du

TIDE: Task-Isolated Diffusion for Unified Video Editing and Generation

arXiv:2606.08260v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers have driven rapid progress in video generation and editing, yet these capabilities are still handled by separa

Training-Inference Kernel Contracts: Bounding Divergence in Post-Training and Deployment

arXiv:2606.07581v1 Announce Type: cross Abstract: A modern post-training pipeline often writes one symbol for its policy, pi_theta, while evaluating it through two different programs: a training kerne

Transition-Based Digital Twin Modelling for Alzheimer's Disease under Sparse Longitudinal Data

arXiv:2606.09671v1 Announce Type: cross Abstract: Alzheimer's disease (AD) progression is highly heterogeneous and is typically observed through sparse and irregular longitudinal data, posing challeng

TRUST-SCF: Transformer-based Risk Understanding and Scoring for Transactional Supply Chain Finance

arXiv:2606.08140v1 Announce Type: new Abstract: Supply Chain Finance (SCF) and LendTech platforms need credit scoring systems that respond to evolving transaction behavior, repayment delays, and activ

Trustworthy Visual Predicates for Robust Manipulation Understanding under Degradation

arXiv:2606.08121v1 Announce Type: new Abstract: Manipulation understanding requires reliable relational evidence, such as contact, support, containment, motion coupling, grasp, release, and active-han

Hardware

TUDSR: Twice Upsampling-Diffusion for Higher Super-Resolution

arXiv:2606.09608v1 Announce Type: new Abstract: Diffusion-based generative models have achieved remarkable success in real-world image super-resolution (SR). With tiled diffusion techniques, these mod

hardwarearxiv-cs-cv