Search: “research”

Walsh-Hadamard Neural Operators for Solving PDEs with Discontinuous Coefficients

arXiv:2511.07347v2 Announce Type: replace-cross Abstract: Neural operators have emerged as powerful tools for learning solution operators of partial differential equations (PDEs). However, standard sp

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Warm-starting active-set solvers using graph neural networks

DGX agent

arXiv:2511.13174v2 Announce Type: replace Abstract: Quadratic programming (QP) solvers are widely used in real-time control and optimization, but their computational cost often limits applicability in

researcharxiv-cs-lg

20 May 2026

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We’re hiring for Labs! 🧪 If you’re interested in working with us to push forward Continual Learning, pls DM me with a blurb + link to the b…

We’re hiring for Labs! 🧪 If you’re interested in working with us to push forward Continual Learning, pls DM me with a blurb + link to the best Applied Research you’ve done (or even better shipped!) yo

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What Are LLMs Doing to Scientific Communication? Measuring Changes in Writing Practices and Reading Experience

arXiv:2605.19936v1 Announce Type: new Abstract: Has the style of scientific communication changed due to the growing use of large language models in the writing process? We address this question in th

What Machine Learning Can Do for Focusing Aerogel Detectors

arXiv:2312.02652v2 Announce Type: replace-cross Abstract: Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARI

What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code

arXiv:2605.19762v1 Announce Type: new Abstract: Code has become a standard component of modern foundation language model (LM) training, yet its role beyond programming remains unclear. We revisit the

When Does Model Collapse Occur in Structured Interactive Learning?

arXiv:2605.20151v1 Announce Type: new Abstract: The proliferation of generative artificial intelligence has given rise to an interactive learning environment, where model parameters are continuously u

When the Majority Votes Wrong, the Intervention Timing for Test-Time Reinforcement Learning Hides in the Extinction Window

arXiv:2605.19444v1 Announce Type: cross Abstract: Test-time reinforcement learning (TTRL) reports substantial accuracy gains on mathematical reasoning benchmarks using majority vote as a pseudo-label

Where Does Authorship Signal Emerge in Encoder-Based Language Models?

arXiv:2605.19908v1 Announce Type: new Abstract: Authorship attribution models fine-tuned with the same pretrained encoder, data, and loss can differ four-fold in performance depending only on their sc

White-Balance First, Adjust Later: Cross-Camera Color Constancy via Vision-Language Evaluation

arXiv:2605.19613v1 Announce Type: new Abstract: Color constancy aims to keep object colors consistent under varying illumination. Cross-camera generalization in color constancy remains challenging bec

Within one 24 hour period, Trump: - got out of a $100 million IRS fine - secured 'immunity' from all future tax investigations for his famil…

Within one 24 hour period, Trump: - got out of a 100 million IRS fine - secured 'immunity' from all future tax investigations for his family and friends - created a 1.8 billion slush fund for lawbreak

researchyann-lecun--x

X-Ray cardiac angiographic vessel segmentation based on pixel classification using machine learning and region growing

arXiv:2605.20073v1 Announce Type: new Abstract: This work proposes a pixel-classification approach for vessel segmentation in x-ray angiograms. The proposal uses textural features such as anisotropic

XFlowMap: Cross-Scale Generalization and Mapping of Massive Origin-Destination Data

arXiv:2605.18777v1 Announce Type: cross Abstract: Mapping large origin-destination (OD) datasets remains challenging because flow maps become cluttered, meaningful patterns occur at multiple spatial s

3D Densification for Multi-Map Monocular VSLAM in Endoscopy

arXiv:2503.14346v3 Announce Type: replace Abstract: Multi-map Sparse Monocular visual Simultaneous Localization and Mapping applied to monocular endoscopic sequences has proven efficient to robustly r

A Conditional U-Net Pipeline with Pre- and Post-Processing for Aerial RGB-to-Thermal Image Translation

arXiv:2605.17564v1 Announce Type: new Abstract: Paired RGB-thermal data has shown significant utility across a range of applications, including image fusion, object tracking, and anomaly detection; ho

A Dataset for the Recognition of Historical and Handwritten Music Scores in Western Notation

arXiv:2605.18436v1 Announce Type: new Abstract: A large amount of musical heritage has been digitised by memory institutions: libraries, museums, and archives. Nevertheless, the field of Optical Music

A Dexterous and Compliant Gripper With Soft Hydraulic Actuation for Microgravity Manipulation

arXiv:2605.17851v1 Announce Type: new Abstract: Astrobee's existing one-degree-of-freedom (DOF) underactuated compliant claw gripper enables perching on the International Space Station (ISS), but prov

researcharxiv-cs-ro

A Distributional View for Visual Mechanistic Interpretability: KL-Minimal Soft-Constraint Principle

arXiv:2605.17504v1 Announce Type: cross Abstract: Most current paradigms in visual mechanistic interpretability (MI) remain confined to interpreting internal units of the vision model via heuristic me

A Holistic Method for Superquadric Fitting Using Unsupervised Clustering Analysis

arXiv:2605.16779v1 Announce Type: cross Abstract: This work presents a novel method for fitting superquadrics to point clouds under the contamination of noise and outliers, which has many applications

A More Word-like Image Tokenization for MLLMs

arXiv:2605.17954v1 Announce Type: cross Abstract: Modern multimodal large language models (MLLMs) typically keep the language model fixed and train a visual projector that maps the pixels into a seque

A neurosymbolic Approach with Epistemic Deep Learning for Hierarchical Image Classification

arXiv:2605.16383v1 Announce Type: cross Abstract: Deep neural networks achieve high accuracy on image classification tasks. Yet, they often produce overconfident predictions as which fail to express e

A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?

arXiv:2605.18666v1 Announce Type: new Abstract: Gradient-based adversarial attacks subtly manipulate inputs of Machine Learning (ML) models to induce incorrect predictions. This paper investigates whe

A Novel Model for 3D Motion Planning for a Generalized Dubins Vehicle with Pitch and Yaw Rate Constraints

arXiv:2509.24143v2 Announce Type: replace Abstract: In this paper, we propose a new modeling approach and a fast algorithm for 3D motion planning, applicable for fixed-wing unmanned aerial vehicles. T

researcharxiv-cs-ro

A Practical Noise2Noise Denoising Pipeline for High-Throughput Raman Spectroscopy

arXiv:2605.18511v1 Announce Type: new Abstract: A lightweight and reproducible denoising pipeline for high-throughput Raman spectroscopy is presented. The approach relies on a one-dimensional convolut

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability

arXiv:2605.18750v1 Announce Type: cross Abstract: Pipeline parallelism is a key technique for scaling large-model training, but modern workloads exhibit runtime variability in computation and communic

A semantic mutation metric for metamorphic relation adequacy in scientific computing programs

arXiv:2605.17437v1 Announce Type: cross Abstract: Context. Metamorphic Testing addresses the test-oracle problem in scientific computing, but classical Mutation Score operates on syntactic AST mutatio

A simple approach for biometrics: Finger-knuckle prints recognition based on a Sobel filter and similarity measures

arXiv:2605.17673v1 Announce Type: new Abstract: The objective of this work is to propose a novel methodology for the finger knuckle print recognition, which is essentially a digital photo of the finge

A Structural Threshold in Decision Capacity Governs Collapse in Self-Play Reinforcement Learning

arXiv:2605.16315v1 Announce Type: cross Abstract: We show that a threshold in decision capacity determines whether self-play reinforcement learning agents collapse under asymmetric rule perturbations.

A Systematic Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation

arXiv:2605.17131v1 Announce Type: cross Abstract: Point cloud stands as the most widely adopted format for representing 3D shapes and scenes due to its simplicity and geometric fidelity. However, its

A Theory of Training Profit-Optimal LLMs

arXiv:2605.16430v1 Announce Type: cross Abstract: Scaling LLMs requires tremendous computational resources, and recent advances in AI have gone hand in hand with massive amounts of capital expenditure

A Unified Framework for Data-Free One-Step Sampling via Wasserstein Gradient Flows

arXiv:2605.17808v1 Announce Type: new Abstract: We develop a unified theoretical framework for data-free one-step sampling from unnormalized target distributions based on Wasserstein gradient flows. F

A Unified Framework for Structured Flow Modeling: From Continuous Fields to Data-Driven Representations

arXiv:2605.18250v1 Announce Type: cross Abstract: Many dynamical systems can be described in terms of structured flows combining source/sink behavior, cyclic dynamics, and topology-constrained transpo

AASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge

arXiv:2408.17352v2 Announce Type: replace-cross Abstract: Automatic Speaker Verification (ASV) systems, which identify speakers based on their voice characteristics, have numerous applications, such a

Accelerating Inference for Multilayer Neural Networks with Quantum Computers

arXiv:2510.07195v2 Announce Type: replace-cross Abstract: Fault-tolerant Quantum Processing Units (QPUs) promise to deliver exponential speed-ups in select computational tasks, yet their integration i

Accelerating Redshift-Conditioned Galaxy Image Synthesis with One-step Generative Modeling

arXiv:2605.17546v1 Announce Type: cross Abstract: Understanding galaxy morphology evolution across cosmic time requires models that can generate realistic galaxy populations conditioned on redshift. I

ACE: Self-Evolving LLM Coding Framework via Adversarial Unit Test Generation and Preference Optimization

arXiv:2605.16299v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at code generation but remain heavily reliant on large-scale annotated solutions and verification-based supervision

Achieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization

arXiv:2310.07983v5 Announce Type: replace Abstract: The ProxSkip algorithm for distributed optimization is gaining increasing attention due to its effectiveness in reducing communication. However, exi

ACIL: Auto Chain of Thoughts for In-Context Learning

arXiv:2605.17088v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have shown that Chain-of-Thought (CoT) reasoning can substantially improve performance on complex reason

Active Defense Against False Data Injection Attacks in Robotic Manipulators

arXiv:2605.17950v1 Announce Type: new Abstract: Robotic systems are vulnerable to False Data Injection Attacks (FDIAs), where adversaries corrupt sensor signals to gain malicious control. Feedback lin

researcharxiv-cs-ro

Active learning for photonic crystals

arXiv:2601.16287v3 Announce Type: replace-cross Abstract: Active learning for photonic crystals explores the integration of analytic approximate Bayesian last layer neural networks (LL-BNNs) with unce

AMARIS: A Memory-Augmented Rubric Improvement System for Rubric-Based Reinforcement Learning

arXiv:2605.18592v1 Announce Type: cross Abstract: Rubric-based reward shaping is an effective method for fine-tuning LLMs via RL, where structured rubrics decompose standard outcome rewards into multi

AMORE: Adaptive Multi-Output Operator Network for Stiff Chemical Kinetics

arXiv:2510.12999v2 Announce Type: replace Abstract: Time integration of stiff systems is a primary source of computational cost in combustion, hypersonics, and other reactive transport systems. This s

AMS-HD: Hyperdimensional Computing for Real-Time and Energy-Efficient Acute Mountain Sickness Detection

arXiv:2602.08916v2 Announce Type: replace-cross Abstract: Objective: Acute mountain sickness (AMS) is the most prevalent altitude illness, affecting unacclimatized individuals ascending above 2,500 m

An Approximation Algorithm for Graph Label Selection

arXiv:2605.18623v1 Announce Type: cross Abstract: In the graph label selection problem, one is given an n-vertex graph and a budget k, and seeks to select k vertices whose labels enable accurate predi

An Efficient Machine Learning-based Framework for Detection and Prevention of Frauds in Telecom Networks

arXiv:2605.17245v1 Announce Type: cross Abstract: Telecommunication fraud is an acute problem that leads to substantial material losses and compromises the reliability of telecom systems worldwide. On

An Information-Theoretic Criterion for Efficient Data Synthesis

arXiv:2605.16379v1 Announce Type: cross Abstract: Synthetic data becomes crucial for large language model training, but its effectiveness is highly inconsistent. We provide an information-theoretic ac

Analyzing Error Propagation in Korean Spoken QA with ASR-LLM Cascades

arXiv:2605.17443v1 Announce Type: new Abstract: We analyze how automatic speech recognition (ASR) errors propagate through ASR-LLM cascades in Korean spoken question answering (SQA), focusing on downs

Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimization

arXiv:2405.14657v2 Announce Type: replace Abstract: Preferential Bayesian optimization (PBO) learns latent utilities from pairwise comparisons, but most existing methods assume homoscedastic compariso