Search: “research”

Modeling, Control and Self-sensing of Dielectric Elastomer Soft Actuators: A Review

arXiv:2604.17199v1 Announce Type: new Abstract: Dielectric elastomer actuators (DEAs) have garnered extensive attention especially in soft robotic applications over the past few decades owing to the a

MoE-nD: Per-Layer Mixture-of-Experts Routing for Multi-Axis KV Cache Compression

DGX agent

arXiv:2604.17695v1 Announce Type: cross Abstract: KV cache memory is the dominant bottleneck for long-context LLM inference. Existing compression methods each act on a single axis of the four-dimensio

researcharxiv-cs-cl

21 Apr 2026

Multi-Beholder: Biomarker Prediction for Low-Grade Glioma with Multiple Instance Learning and One-Class Classification

arXiv:2310.07464v2 Announce Type: replace-cross Abstract: Biomarker detection is an indispensable part of the diagnosis and treatment of low-grade glioma (LGG). However, current LGG biomarker detectio

Multi-Label Phase Diagram Prediction in Complex Alloys via Physics-Informed Graph Attention Networks

arXiv:2604.16468v1 Announce Type: new Abstract: Accurate phase equilibria are foundational to alloy design because they encode the underlying thermodynamics governing stability, transformations, and p

Multi-Scale Reversible Chaos Game Representation: A Unified Framework for Sequence Classification

arXiv:2604.18477v1 Announce Type: new Abstract: Biological classification with interpretability remains a challenging task. For this, we introduce a novel encoding framework, Multi-Scale Reversible Ch

Multi-stage Planning for Multi-target Surveillance using Aircrafts Equipped with Synthetic Aperture Radars Aware of Target Visibility

arXiv:2604.16962v1 Announce Type: new Abstract: Generating trajectories for synthetic aperture radar (SAR)-equipped aircraft poses significant challenges due to terrain constraints, and the need for s

Multilingual Training and Evaluation Resources for Vision-Language Models

arXiv:2604.18347v1 Announce Type: new Abstract: Vision Language Models (VLMs) achieved rapid progress in the recent years. However, despite their growth, VLMs development is heavily grounded on Englis

Multimodal Fusion of Histopathology Images and Electronic Health Records for Early Breast Cancer Diagnosis

arXiv:2604.17122v1 Announce Type: new Abstract: Breast cancer is a leading cause of cancer-related mortality worldwide, and timely accurate diagnosis is critical to improving survival outcomes. While

MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding

arXiv:2505.20715v2 Announce Type: replace-cross Abstract: Video temporal understanding is crucial for multimodal large language models (MLLMs) to reason over events in videos. Despite recent advances

MuSteerNet: Human Reaction Generation from Videos via Observation-Reaction Mutual Steering

arXiv:2603.20187v2 Announce Type: replace Abstract: Video-driven human reaction generation aims to synthesize 3D human motions that directly react to observed video sequences, which is crucial for bui

Negative Momentum for Convex-Concave Optimization

arXiv:2604.17145v1 Announce Type: cross Abstract: This paper revisits momentum in the context of min-max optimization. Momentum is a celebrated mechanism for accelerating gradient dynamics in settings

Neural Adjoint Method for Meta-optics: Accelerating Volumetric Inverse Design via Fourier Neural Operators

arXiv:2604.17425v1 Announce Type: new Abstract: Meta-optics promises compact, high-performance imaging and color routing. However, designing high-performance structures is a high-dimensional optimizat

Neural Network-Based Adaptive Event-Triggered Control for Dual-Arm Unmanned Aerial Manipulator Systems

arXiv:2604.17048v1 Announce Type: new Abstract: This paper investigates the control problem of dual-arm unmanned aerial manipulator systems (DAUAMs). Strong coupling between the dual-arm and the multi

Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization

arXiv:2401.15604v4 Announce Type: replace Abstract: Diffusion models have become a leading paradigm in generative AI, with score estimation via denoising score matching as a central component. While r

Neural Operator: Is data all you need to model the world? An insight into the paradigm of data-driven scientific ML

arXiv:2301.13331v3 Announce Type: replace-cross Abstract: Numerical approximations of partial differential equations (PDEs) are routinely employed to formulate the solution of physics, engineering, an

Neuroscience Inspired Graph Operators Towards Edge-Deployable Virtual Sensing for Irregular Geometries

arXiv:2604.16722v1 Announce Type: new Abstract: Predicting full-field physics through the real-time virtual sensing of engineering systems can enhance limited physical sensors but often requires spars

New Fourth-Order Grayscale Indicator-Based Telegraph Diffusion Model for Image Despeckling

arXiv:2509.26010v2 Announce Type: replace Abstract: Second-order PDE models have been widely used for suppressing multiplicative noise, but they often introduce blocky artifacts in the early stages of

NI Sampling: Accelerating Discrete Diffusion Sampling by Token Order Optimization

arXiv:2604.18471v1 Announce Type: new Abstract: Discrete diffusion language models (dLLMs) have recently emerged as a promising alternative to traditional autoregressive approaches, offering the flexi

No One Fits All: From Fixed Prompting to Learned Routing in Multilingual LLMs

arXiv:2604.16937v1 Announce Type: new Abstract: Translation-based prompting is widely used in multilingual LLMs, yet its effectiveness varies across languages and tasks. We evaluate prompting strategi

No-Worse Context-Aware Decoding: Preventing Neutral Regression in Context-Conditioned Generation

arXiv:2604.16686v1 Announce Type: new Abstract: Large language models (LLMs) can answer questions and summarize documents when conditioned on external contexts (e.g., retrieved evidence), yet context

Non-Stationarity in the Embedding Space of Time Series Foundation Models

arXiv:2604.16428v1 Announce Type: new Abstract: Time series foundation models (TSFMs) are widely used as generic feature extractors, yet the notion of non-stationarity in their embedding spaces remain

NPCNet: Navigator-Driven Pseudo Text for Deep Clustering of Early Sepsis Phenotyping

arXiv:2602.03562v2 Announce Type: replace Abstract: Electronic Health Records (EHRs) provide high-dimensional temporal data essential for patient modeling; however, conventional algorithmic approaches

OASIS: On-Demand Hierarchical Event Memory for Streaming Video Reasoning

arXiv:2604.17052v1 Announce Type: new Abstract: Streaming video reasoning requires models to operate in a setting where history grows without bound while meaningful evidence remains scarce. In such a

OD3: Optimization-free Dataset Distillation for Object Detection

arXiv:2506.01942v2 Announce Type: replace Abstract: Training large neural networks on large-scale datasets requires substantial computational resources, particularly for dense prediction tasks such as

On Different Notions of Redundancy in Conditional-Independence-Based Discovery of Graphical Models

arXiv:2502.08531v3 Announce Type: replace Abstract: Conditional-independence-based discovery uses statistical tests to identify a graphical model that represents the independence structure of variable

On the Interpolation Effect of Score Smoothing in Diffusion Models

arXiv:2502.19499v3 Announce Type: replace Abstract: Diffusion models have achieved remarkable progress in various domains with an intriguing ability to produce new data that do not exist in the traini

On The Mathematics of the Natural Physics of Optimization

arXiv:2604.17645v1 Announce Type: cross Abstract: A number of optimization algorithms have been inspired by the physics of Newtonian motion. Here, we ask the question: do algorithms themselves obey so

On the Robustness of LLM-Based Dense Retrievers: A Systematic Analysis of Generalizability and Stability

arXiv:2604.16576v1 Announce Type: cross Abstract: Decoder-only large language models (LLMs) are increasingly replacing BERT-style architectures as the backbone for dense retrieval, achieving substanti

On the Sample Complexity of Learning for Blind Inverse Problems

arXiv:2512.23405v4 Announce Type: replace Abstract: Blind inverse problems arise in many experimental settings where both the signal of interest and the forward operator are (partially) unknown. In th

On the Theory of Continual Learning with Gradient Descent for Neural Networks

arXiv:2510.05573v2 Announce Type: replace-cross Abstract: Continual learning, the ability of a model to adapt to an ongoing sequence of tasks without forgetting earlier ones, is a central goal of arti

One of the most jarring things about current AI is its lack of introspection ability and metacognition. It doesn't know what it doesn't know…

researchfrancois-chollet--x

One of the most jarring things about current AI is its lack of introspection ability and metacognition. It doesn't know what it doesn't know, how it knows, or how it could find out. It's a one-way sys

One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection

arXiv:2604.18393v1 Announce Type: new Abstract: Diffusion models have achieved outstanding performance in unsupervised industrial anomaly detection (uIAD) by learning a manifold of normal data under t

ONTO: A Token-Efficient Columnar Notation for LLM Input Optimization

arXiv:2604.17512v1 Announce Type: new Abstract: Serialization formats designed for document interchange impose structural overhead that becomes prohibitive when large language models consume operation

Optimal control of differentially flat underactuated planar robots in the perspective of oscillation mitigation

arXiv:2603.15528v2 Announce Type: replace Abstract: Underactuated robots are characterized by a larger number of degrees of freedom than actuators and if they are designed with a specific mass distrib

ORSIFlow: Saliency-Guided Rectified Flow for Optical Remote Sensing Salient Object Detection

arXiv:2603.28584v2 Announce Type: replace Abstract: Optical Remote Sensing Image Salient Object Detection (ORSI-SOD) remains challenging due to complex backgrounds, low contrast, irregular object shap

Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Rendering

arXiv:2508.14461v3 Announce Type: replace Abstract: While multi-step diffusion models have advanced both forward and inverse rendering, existing approaches often treat these problems independently, le

P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist

arXiv:2601.02986v2 Announce Type: replace Abstract: Recent approaches in personalized reward modeling have primarily focused on leveraging user interaction history to align model judgments with indivi

PA-TCNet: Pathology-Aware Temporal Calibration with Physiology-Guided Target Refinement for Cross-Subject Motor Imagery EEG Decoding in Stroke Patients

arXiv:2604.16554v1 Announce Type: new Abstract: Stroke patient cross-subject electroencephalography (EEG) decoding of motor imagery (MI) brain-computer interface (BCI) is essential for motor rehabilit

Parkinson's Disease Detection via Self-Supervised Dual-Channel Cross-Attention on Bilateral Wrist-Worn IMU Signals

arXiv:2604.18372v1 Announce Type: new Abstract: Parkinson's disease (PD) is a chronic neurodegenerative disease. It shows multiple motor symptoms such as tremor, bradykinesia, postural instability, fr

PCM-NeRF: Probabilistic Camera Modeling for Neural Radiance Fields under Pose Uncertainty

arXiv:2604.17831v1 Announce Type: new Abstract: Neural surface reconstruction methods typically treat camera poses as fixed values, assuming perfect accuracy from Structure-from-Motion (SfM) systems.

Pearmut: Human Evaluation of Translation Made Trivial

arXiv:2601.02933v3 Announce Type: replace Abstract: Human evaluation is the gold standard for multilingual NLP, but is often skipped in practice and substituted with automatic metrics because it is no

Periodic Steady-State Control of a Handkerchief-Spinning Task Using a Parallel Anti-Parallelogram Tendon-driven Wrist

arXiv:2604.17863v1 Announce Type: new Abstract: Spinning flexible objects, exemplified by traditional Chinese handkerchief performances, demands periodic steady-state motions under nonlinear dynamics

Persistence-Augmented Neural Networks

arXiv:2604.08469v2 Announce Type: replace Abstract: Topological Data Analysis (TDA) provides tools to describe the shape of data, but integrating topological features into deep learning pipelines rema

Physics-Informed Graph Neural Networks for Transverse Momentum Estimation in CMS Trigger Systems

arXiv:2507.19205v2 Announce Type: replace Abstract: Real-time particle transverse momentum (p_T) estimation in high-energy physics demands algorithms that are both efficient and accurate under strict

Physics-Informed Tracking (PIT)

arXiv:2604.16895v1 Announce Type: new Abstract: We propose Physics-Informed Tracking (PIT), a video-based framework for tracking a single particle from video, where a neural network autoencoder locali

Planning Smooth and Safe Control Laws for a Unicycle Robot Among Obstacles

arXiv:2604.17212v1 Announce Type: new Abstract: This paper presents a framework for safe navigation of a unicycle point robot to a goal position in an environment populated with obstacles from almost

PoInit-of-View: Poisoning Initialization of Views Transfers Across Multiple 3D Reconstruction Systems

arXiv:2604.16540v1 Announce Type: new Abstract: Poisoning input views of 3D reconstruction systems has been recently studied. However, we identify that existing studies simply backpropagate adversaria

Predicting Blastocyst Formation in IVF: Integrating DINOv2 and Attention-Based LSTM on Time-Lapse Embryo Images

arXiv:2604.16505v1 Announce Type: new Abstract: The selection of the optimal embryo for transfer is a critical yet challenging step in in vitro fertilization (IVF), primarily due to its reliance on th