Search: “research”

Unconventional Hexacopters via Evolution and Learning: Performance Gains and New Insights

arXiv:2505.14129v2 Announce Type: replace Abstract: Evolution and learning have historically been interrelated topics, and their interplay is attracting increased interest lately. The emerging new fac

researcharxiv-cs-ro

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

UniMark: Unified Adaptive Multi-bit Watermarking for Autoregressive Image Generators

DGX agent

arXiv:2604.11843v1 Announce Type: new Abstract: Invisible watermarking for autoregressive (AR) image generation has recently gained attention as a means of protecting image ownership and tracing AI-ge

researcharxiv-cs-cv

15 Apr 2026

Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling

arXiv:2505.17384v2 Announce Type: replace-cross Abstract: Discrete diffusion models have recently shown great promise for modeling complex discrete data, with masked diffusion models (MDMs) offering a

VeriX-Anon: A Multi-Layered Framework for Mathematically Verifiable Outsourced Target-Driven Data Anonymization

arXiv:2604.12431v1 Announce Type: cross Abstract: Organisations increasingly outsource privacy-sensitive data transformations to cloud providers, yet no practical mechanism lets the data owner verify

Vision Transformers Need More Than Registers

arXiv:2602.22394v2 Announce Type: replace Abstract: Vision Transformers (ViTs), when pre-trained on large-scale data, provide general-purpose representations for diverse downstream tasks. However, art

VISTA: Validation-Informed Trajectory Adaptation via Self-Distillation

arXiv:2604.12044v1 Announce Type: cross Abstract: Deep learning models may converge to suboptimal solutions despite strong validation accuracy, masking an optimization failure we term Trajectory Devia

Visual Diffusion Models are Geometric Solvers

arXiv:2510.21697v2 Announce Type: replace Abstract: In this paper we show that visual diffusion models can serve as effective geometric solvers: they can directly reason about geometric problems by wo

Why and When Visual Token Pruning Fails? A Study on Relevant Visual Information Shift in MLLMs Decoding

arXiv:2604.12358v1 Announce Type: new Abstract: Recently, visual token pruning has been studied to handle the vast number of visual tokens in Multimodal Large Language Models. However, we observe that

XANE(3): An E(3)-Equivariant Graph Neural Network for Accurate Prediction of XANES Spectra from Atomic Structures

arXiv:2604.12140v1 Announce Type: new Abstract: We present XANE(3), a physics-based E(3)-equivariant graph neural network for predicting X-ray absorption near-edge structure (XANES) spectra directly f

3D-Anchored Lookahead Planning for Persistent Robotic Scene Memory via World-Model-Based MCTS

arXiv:2604.11302v1 Announce Type: cross Abstract: We present 3D-Anchored Lookahead Planning (3D-ALP), a System 2 reasoning engine for robotic manipulation that combines Monte Carlo Tree Search (MCTS)

3DTV: A Feedforward Interpolation Network for Real-Time View Synthesis

arXiv:2604.11211v1 Announce Type: new Abstract: Real-time free-viewpoint rendering requires balancing multi-camera redundancy with the latency constraints of interactive applications. We address this

A Comparison of Multi-View Stereo Methods for Photogrammetric 3D Reconstruction: From Traditional to Learning-Based Approaches

arXiv:2604.10246v1 Announce Type: new Abstract: Photogrammetric 3D reconstruction has long relied on traditional Structure-from-Motion (SfM) and Multi-View Stereo (MVS) methods, which provide high acc

A Coordinate-Invariant Local Representation of Motion and Force Trajectories for Identification and Generalization Across Coordinate Systems

arXiv:2604.10241v1 Announce Type: new Abstract: Identifying the trajectories of rigid bodies and of interaction forces is essential for a wide range of tasks in robotics, biomechanics, and related dom

researcharxiv-cs-ro

A Deep Generative Approach to Stratified Learning

arXiv:2604.10650v1 Announce Type: cross Abstract: While the manifold hypothesis is widely adopted in modern machine learning, complex data is often better modeled as stratified spaces -- unions of man

A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection

arXiv:2604.10116v1 Announce Type: cross Abstract: Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a s

A Faster Path to Continual Learning

arXiv:2604.11064v1 Announce Type: cross Abstract: Continual Learning (CL) aims to train neural networks on a dynamic stream of tasks without forgetting previously learned knowledge. Among optimization

A-IO: Adaptive Inference Orchestration for Memory-Bound NPUs

arXiv:2604.09752v1 Announce Type: cross Abstract: During the deployment of Large Language Models (LLMs), the autoregressive decoding phase on heterogeneous NPU platforms (e.g., Ascend 910B) faces seve

A Mathematical Explanation of Transformers

arXiv:2510.03989v2 Announce Type: replace-cross Abstract: The Transformer architecture has revolutionized the field of sequence modeling and underpins the recent breakthroughs in large language models

A Minimal Model of Representation Collapse: Frustration, Stop-Gradient, and Dynamics

arXiv:2604.09979v1 Announce Type: cross Abstract: Self-supervised representation learning is central to modern machine learning because it extracts structured latent features from unlabeled data and e

A Modularized Framework for Piecewise-Stationary Restless Bandits

arXiv:2604.10177v1 Announce Type: cross Abstract: We study the piecewise-stationary restless multi-armed bandit (PS-RMAB) problem, where each arm evolves as a Markov chain but mean rewards may change

A molecular clock for writing systems reveals the quantitative impact of imperial power on cultural evolution

arXiv:2604.10957v1 Announce Type: cross Abstract: Writing systems are cultural replicators whose evolution has never been studied quantitatively at global scale. We compile the Global Script Database

A Multi-head Attention Fusion Network for Industrial Prognostics under Discrete Operational Conditions

arXiv:2604.10248v1 Announce Type: new Abstract: Complex systems such as aircraft engines, turbines, and industrial machinery often operate under dynamically changing conditions. These varying operatin

A Progressive Training Strategy for Vision-Language Models to Counteract Spatio-Temporal Hallucinations in Embodied Reasoning

arXiv:2604.10506v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have made significant strides in static image understanding but continue to face critical hurdles in spatiotemporal reason

A Quantitative Definition of Intelligence

arXiv:2604.10873v1 Announce Type: new Abstract: We propose an operational, quantitative definition of intelligence for arbitrary physical systems. The intelligence density of a system is the ratio of

A Structured Clustering Approach for Inducing Media Narratives

arXiv:2604.10368v1 Announce Type: new Abstract: Media narratives wield tremendous power in shaping public opinion, yet computational approaches struggle to capture the nuanced storytelling structures

researcharxiv-cs-cl

A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities

arXiv:2604.11048v1 Announce Type: cross Abstract: Imbuing Large Language Models (LLMs) with specific personas is prevalent for tailoring interaction styles, yet the impact on underlying cognitive capa

A Temporally Augmented Graph Attention Network for Affordance Classification

arXiv:2604.10149v1 Announce Type: cross Abstract: Graph attention networks (GATs) provide one of the best frameworks for learning node representations in relational data; but, existing variants such a

A Triadic Suffix Tokenization Scheme for Numerical Reasoning

arXiv:2604.11582v1 Announce Type: cross Abstract: Standard subword tokenization methods fragment numbers inconsistently, causing large language models (LLMs) to lose positional and decimal structure -

A3-FPN: Asymptotic Content-Aware Pyramid Attention Network for Dense Visual Prediction

arXiv:2604.10210v1 Announce Type: new Abstract: Learning multi-scale representations is the common strategy to tackle object scale variation in dense prediction tasks. Although existing feature pyrami

Absorption and Inertness in Coarse-Grained Arithmetic: A Heuristic Application to the St. Petersburg Paradox

arXiv:2507.12475v2 Announce Type: replace-cross Abstract: The St. Petersburg paradox presents a longstanding challenge in decision theory: its classical expected value diverges, yet no correspondingly

Achieving Skilled and Reliable Daily Probabilistic Forecasts of Wind Power at Subseasonal-to-Seasonal Timescales over France

arXiv:2511.16164v2 Announce Type: replace Abstract: In a growing renewable based energy system, accurate and reliable wind power forecasts are crucial for grid stability, balancing supply and demand a

Active Bayesian Inference for Robust Control under Sensor False Data Injection Attacks

arXiv:2604.11410v1 Announce Type: new Abstract: We present a framework for bridging the gap between sensor attack detection and recovery in cyber-physical systems. The proposed framework models modern

Active Inference with a Self-Prior in the Mirror-Mark Task

arXiv:2604.09673v1 Announce Type: cross Abstract: The mirror self-recognition test evaluates whether a subject touches a mark on its own body that is visible only in a mirror, and is widely used as an

Adaptive H-EFT-VA: A Provably Safe Trajectory Through the Trainability-Expressibility Landscape of Variational Quantum Algorithms

arXiv:2604.10607v1 Announce Type: cross Abstract: H-EFT-VA established a physics-informed solution to the Barren Plateau (BP) problem via a hierarchical EFT UV-cutoff, guaranteeing gradient variance i

Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation

arXiv:2604.10335v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance in math reasoning benchmarks, but their performance varies inconsistently across problems wi

researcharxiv-cs-cl

Adversarial Robustness of Graph Transformers

arXiv:2407.11764v2 Announce Type: replace Abstract: Existing studies have shown that Message-Passing Graph Neural Networks (MPNNs) are highly susceptible to adversarial attacks. In contrast, despite t

Adversarial Video Promotion Against Text-to-Video Retrieval

arXiv:2508.06964v3 Announce Type: replace Abstract: Thanks to the development of cross-modal models, text-to-video retrieval (T2VR) is advancing rapidly, but its robustness remains largely unexamined.

AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation

arXiv:2602.17071v2 Announce Type: replace-cross Abstract: Graph neural networks frequently encounter significant performance degradation when confronted with structural noise or non-homophilous topolo

AEG: A Baremetal Framework for AI Acceleration via Direct Hardware Access in Heterogeneous Accelerators

arXiv:2604.09565v1 Announce Type: cross Abstract: This paper introduces a unified, hardware-independent baremetal runtime architecture designed to enable high-performance machine learning (ML) inferen

Affostruction: 3D Affordance Grounding with Generative Reconstruction

arXiv:2601.09211v2 Announce Type: replace Abstract: This paper addresses the problem of affordance grounding from RGBD images of an object, which aims to localize surface regions corresponding to a te

AHC: Meta-Learned Adaptive Compression for Continual Object Detection on Memory-Constrained Microcontrollers

arXiv:2604.09576v1 Announce Type: new Abstract: Deploying continual object detection on microcontrollers (MCUs) with under 100KB memory requires efficient feature compression that can adapt to evolvin

Safety

AI Organizations are More Effective but Less Aligned than Individual Agents

arXiv:2604.10290v1 Announce Type: new Abstract: AI is increasingly deployed in multi-agent systems; however, most research considers only the behavior of individual models. We experimentally show that

safetyarxiv-cs-ai

AI Patents in the United States and China: Measurement, Organization, and Knowledge Flows

arXiv:2604.10529v1 Announce Type: cross Abstract: We develop a high-precision classifier to measure artificial intelligence (AI) patents by fine-tuning PatentSBERTa on manually labeled data from the U

Ambivalence/Hesitancy Recognition in Videos for Personalized Digital Health Interventions

arXiv:2604.11730v1 Announce Type: new Abstract: Using behavioural science, health interventions focus on behaviour change by providing a framework to help patients acquire and maintain healthy habits

An explicit construction of Kaleidocycles by elliptic theta functions

arXiv:2308.04977v4 Announce Type: replace-cross Abstract: We consider the configuration space of ordered points on the two-dimensional sphere that satisfy a specific system of quadratic equations. We

researcharxiv-cs-ro

An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMs

arXiv:2406.11290v3 Announce Type: replace-cross Abstract: Relevance and utility are two frequently used measures to evaluate the effectiveness of an information retrieval (IR) system. Relevance emphas

An overview of condensation phenomenon in deep learning

arXiv:2504.09484v2 Announce Type: replace Abstract: In this paper, we provide an overview of a common phenomenon, condensation, observed during the nonlinear training of neural networks: During the no

Analytical Modeling and Correction of Distance Error in Homography-Based Ground-Plane Mapping

arXiv:2604.10805v1 Announce Type: new Abstract: Accurate distance estimation from monocular cameras is essential for intelligent monitoring systems. In many deployments, image coordinates are mapped t