Search: “research”

DP-BOA: Dirichlet-Process Birth-or-Assign for On-the-Fly Category Discovery

arXiv:2607.13504v1 Announce Type: new Abstract: On-the-fly category discovery requires deciding for each incoming test sample whether to assign it to an existing category or spawn a new one. Existing

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Research

DriveFace: A Cross-Spectral Through-Glass Face Dataset for On-the-Move Vehicular Border Control

DGX agent

arXiv:2607.13515v1 Announce Type: new Abstract: The continuous growth in cross-border mobility places increasing pressure on existing border control infrastructures, motivating on-the-move biometric a

researcharxiv-cs-cv

16 Jul 2026

Efficiency, Feasibility, and Incentive-Awareness in Constrained Online Resource Allocation

arXiv:2507.09473v2 Announce Type: replace-cross Abstract: We study the dynamic allocation of indivisible resources to strategic agents under long-term constraints, where the planner aims to maximize s

Efficient Computing for Medical Image Acquisition and Reconstruction

arXiv:2607.13204v1 Announce Type: cross Abstract: Medical imaging systems such as CT, MRI, PET, and SPECT do not directly acquire images. Instead, they measure physical signals that encode anatomical

EM-GANSim: Real-time and Accurate EM Simulation Using Conditional GANs for 3D Indoor Scenes

arXiv:2405.17366v3 Announce Type: replace Abstract: We present a novel machine-learning (ML) approach (EM-GANSim) for real-time electromagnetic (EM) propagation that is used for wireless communication

Explainable Artificial Intelligence for Anomaly Detection in Banking Transactions: An Internal Audit Perspective

arXiv:2607.13469v1 Announce Type: cross Abstract: The banking sector increasingly relies on automated systems to monitor electronic transactions for signs of fraud, yet conventional rule-based approac

EZSMT Version 3, Matured

arXiv:2607.13344v1 Announce Type: new Abstract: Constraint Answer Set Programming (CASP) is a hybrid reasoning paradigm that combines Answer Set Programming (ASP) with Constraint Processing and Satisf

Factorized Spectral Representations for Reinforcement Learning

arXiv:2607.13498v1 Announce Type: new Abstract: Learning a compact model of the world from interaction data is central to sample-efficient deep reinforcement learning. Spectral representation methods

From Pixels to States: Rethinking Interactive World Models as Game Engines

arXiv:2607.14076v1 Announce Type: new Abstract: Building interactive worlds that respond coherently to player actions has long been a shared goal of computer graphics, games, and artificial intelligen

GFlowRL: Scaling Distribution-Matching RL to Large Language Models

arXiv:2607.13394v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) offer a promising alternative to reward-maximizing reinforcement learning (RL) for large reasoning models, encour

Graph Partitioning with Demands: Generalized Conductance and its Applications

arXiv:2607.13218v1 Announce Type: cross Abstract: In this work, we study various graph partitioning problems under a general demand model. In each such task, we are given a graph G=(V,E,c,w) with a ca

Greedy Volume Maximization of Gradient Embeddings for Long-Tailed Frame-Level Bioacoustic Active Learning

arXiv:2607.13555v1 Announce Type: cross Abstract: Bioacoustic call-type classification relies on costly expert annotation. Active learning can reduce this burden by selecting a small batch of segments

Hierarchical F-Clustering: Approximation and Hardness of Clustering into Trees and Bounded Diameter Graphs

arXiv:2607.13217v1 Announce Type: cross Abstract: Consider the following variation on the Hierarchical Clustering problem: Usually, while building a hierarchical clustering, one recursively partitions

HIVE-3D: Hierarchical Voxel Enhancement for High-Quality 3D Scene Generation

arXiv:2607.13468v1 Announce Type: new Abstract: Recently, a line of works can generate impressive 3D objects from a single image, but they are limited by restricted representation resolution, making t

How the Hessian-Spectrum of Neural Networks Depends on Data

arXiv:2607.13631v1 Announce Type: new Abstract: The Hessian matrix is an important quantity of interest when it comes to studying the loss landscape and optimization dynamics in deep learning, as well

Improving Map Consistency in Graph-Based LiDAR SLAM Through Information-Aware Odometry and Retroactive Loop Closure

arXiv:2607.13516v1 Announce Type: new Abstract: High-quality maps are fundamental for robotics tasks such as navigation and planning. Although modern graph-based LiDAR SLAM systems achieve good trajec

researcharxiv-cs-ro

Improving Medical Image Generative Models with Frechet Distance Loss

arXiv:2607.13300v1 Announce Type: new Abstract: Diffusion generative models have demonstrated immense potential for synthetic medical image generation. However, these models often struggle to capture

Just-In-Time Scene Graph Growth: Combating Perceptual Saturation in Long-Horizon Robotics

arXiv:2607.13245v1 Announce Type: new Abstract: While 3D Scene Graphs (3DSGs) provide crucial structured representations for embodied agents, conventional Ahead-of-Time, build-everything-then-filter p

Kaleido: Algorithm-Hardware Co-Design for Video Diffusion Transformers by Exploiting Latent Space Correlations

arXiv:2607.13770v1 Announce Type: cross Abstract: Video diffusion transformers (vDiTs) generate high quality video but introduce extremely high compute cost due to the long diffusion timesteps and sel

Kepler-Encoder-v0.1: Towards a Multimodal Embedding Model for Robots

arXiv:2607.13522v1 Announce Type: cross Abstract: A robot must understand the state of its own body, but a camera sees only part of it. Force and contact leave almost no trace in a single frame, and r

Koopman-driven grip force prediction through EMG sensing

arXiv:2409.17340v2 Announce Type: replace-cross Abstract: Loss of hand function due to conditions like stroke or multiple sclerosis significantly impacts daily activities. Robotic rehabilitation provi

Lag Operator SSMs: A Geometric Framework for Structured State Space Modeling

arXiv:2512.18965v2 Announce Type: replace Abstract: Structured State Space Models (SSMs), which are at the heart of the recently popular Mamba architecture, are powerful tools for sequence modeling. H

LaME: Learning to Think in Latent Space for Multimodal Embedding via Information Bottleneck

arXiv:2606.13061v2 Announce Type: replace Abstract: Reasoning-driven universal multimodal embedding has advanced rapidly by introducing Chain-of-Thought (CoT) reasoning into the embedding pipeline. De

Learned Pairwise Deep Dual-Optimal Inequalities for Stabilizing Column Generation

arXiv:2607.13373v1 Announce Type: cross Abstract: Column generation (CG) is central to many large-scale optimization algorithms, including branch-price-and-cut methods for vehicle routing problems, bu

Left-right asymmetry in predicting brain activity from LLMs' representations emerges with their formal linguistic competence

arXiv:2602.12811v2 Announce Type: replace-cross Abstract: When humans and large language models (LLMs) process the same text, activations in the LLMs correlate with brain activity measured, e.g., with

Leveraging Differentiable PDE Solvers for Semi-Neural Spatial Reconstruction From Sparse Measurements

arXiv:2601.20496v2 Announce Type: replace-cross Abstract: Generating dense physical fields from sparse measurements is a fundamental question in sampling, signal processing, and many other application

Leveraging unlabelled data for generalizable neural population decoding

arXiv:2607.14086v1 Announce Type: new Abstract: Robust and accurate neural decoders are integral to neurotechnologies such as brain-computer interfaces and closed-loop experiments. Recent work has sho

Linear Independent Component Analysis via Optimal Transport

arXiv:2607.14081v1 Announce Type: new Abstract: Linear Independent Component Analysis (ICA) recovers jointly independent source signals from their linear mixtures. To achieve this, classical ICA algor

LLM-Guided Reinforcement Learning for Audio-Visual Speech Enhancement

arXiv:2603.13952v3 Announce Type: replace-cross Abstract: In existing Audio-Visual Speech Enhancement (AVSE) methods, objectives such as Scale-Invariant Signal-to-Noise Ratio (SI-SNR) and Mean Squared

Maximally Robust Satisficing Bayesian Optimization

arXiv:2607.13652v1 Announce Type: new Abstract: Many design tasks can be cast as black-box function optimization, enabling use of Bayesian optimization to find an ideal design with minimal number of t

MGFace: Mask-Gated Face Matching via Conditional Similarity Routing

arXiv:2607.13187v1 Announce Type: new Abstract: Face identification has achieved remarkable performance under normal conditions. Yet, its accuracy often degrades significantly when query faces are par

Min-Max Regret Task Allocation and Planning of Heterogeneous Multi-Robot System in Partially Known Environments

arXiv:2607.13403v1 Announce Type: new Abstract: Efficient task allocation for large-scale Heterogeneous Multi-Robot Systems (HMRS) is critical, yet dealing with complex temporal logic tasks in partial

researcharxiv-cs-ro

MultiAnimate: A Unified Framework for Controllable Multi-Character Animation

arXiv:2607.13415v1 Announce Type: new Abstract: Recent advances in generative models and technological innovations have significantly addressed the fundamental challenges of character image animation.

Multimodal Empirical Bayes Variational Autoencoders for Joint Longitudinal and Time-to-Event Modeling

arXiv:2607.13984v1 Announce Type: cross Abstract: Longitudinal tumor measurements, dropout information, and genetic covariates provide complementary information about treatment response, but integrati

New universal operator approximation theorem for encoder-decoder architectures

arXiv:2503.24092v2 Announce Type: replace-cross Abstract: Motivated by the rapidly growing field of mathematics for operator approximation with neural networks, we present a novel universal operator a

Nexus: Native Mesh Generation with Diffusion

arXiv:2607.13563v1 Announce Type: new Abstract: Generating high-quality triangle meshes is essential for film, gaming, and interactive 3D applications. Mainstream methods rely on mesh serialization an

Not All Retrievals are Useful: Cross-Attention for Input-Aware RAG in Time Series Forecasting

arXiv:2603.14709v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enhances zero-shot time series (TS) forecasting by leveraging external knowledge bases, yet existing approaches

Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer

arXiv:2505.14303v3 Announce Type: replace-cross Abstract: Using Resistive Random Access Memory (RRAM) crossbars in Computing-in-Memory (CIM) architectures offers a promising solution to overcome the v

OriginBlame: Record- and Token-Level Data Provenance for AI Training Datasets

arXiv:2607.13037v1 Announce Type: new Abstract: When a data contributor requests removal, model trainers face a practical gap: unlearning algorithms require a forget set, yet no tool can locate which

Parallel gradient boosting for flexible estimation of conditional distributions

arXiv:2607.13550v1 Announce Type: cross Abstract: Boosting is one of the most successful learning techniques for standard classification and regression tasks. Its extension to multi-output prediction

PersGuard: Preventing Malicious Personalization in Text-to-Image Diffusion Models via Model Backdoors

arXiv:2502.16167v2 Announce Type: replace-cross Abstract: Diffusion models (DMs) have advanced text-to-image (T2I) synthesis, yet their personalization capabilities raise serious privacy and copyright

Plausible Deniability Guarantees for Whistleblowers

arXiv:2607.13928v1 Announce Type: cross Abstract: Whistleblowers are a key safeguard against organizational wrongdoing, but the threat of retaliation deters reporting. Existing whistleblower-protectio

PlumeQuant: Uncertainty-aware consistency assessment of methane plume masks and emission-rate estimates

arXiv:2607.13945v1 Announce Type: new Abstract: Imaging spectrometers increasingly distribute source-resolved methane plume products in which the plume mask, integrated mass enhancement (IME), plume l

Post-Disaster Affected Area Segmentation with a Vision Transformer (ViT)-based EVAP Model using Sentinel-2 and Formosat-5 Imagery

arXiv:2507.16849v3 Announce Type: replace-cross Abstract: We propose a vision transformer (ViT)-based deep learning framework to refine disaster-affected area segmentation from remote sensing imagery,

Power Homotopy for Zeroth-Order Non-Convex Optimizations

arXiv:2511.13592v2 Announce Type: replace-cross Abstract: The existing method of GS-PowerOpt solves the non-convex optimization problem of the form max_{oldsymbol{x} in R^d} f(oldsymbol{x}) through ma

Precomputing the Future-Offset Average in TriAttention

arXiv:2607.13051v1 Announce Type: cross Abstract: TriAttention is a recent method for shrinking the KV cache of long-reasoning LLMs: it scores each cached key by how much attention it is likely to rec

Probabilistic Extension of Neuro-Symbolic AGI Robots based on Belnap's Typed Intensional FOL

arXiv:2607.13073v1 Announce Type: new Abstract: Neuro-symbolic AI based on IFOL_B is a way to combine neural learning and symbolic reasoning to overcome limitations of purely neural systems (like lack

Prospective clinical indication, post-hoc report leakage, and fusion design in multi-image chest radiograph classification: a patient-clustered evaluation

arXiv:2607.13800v1 Announce Type: cross Abstract: Chest radiograph datasets often combine multiple images with Clinical Indication, Findings, and Impression, although these inputs are produced at diff