Search: “research”

(How) Learning Rates Regulate Catastrophic Overtraining

arXiv:2604.13627v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) is a common first stage of LLM post-training, teaching the model to follow instructions and shaping its behavior as a hel

HUANet: Hard-Constrained Unrolled ADMM for Constrained Convex Optimization

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DGX agent

arXiv:2604.13179v1 Announce Type: cross Abstract: This paper presents HUANet, a constrained deep neural network architecture that unrolls the iterations of the Alternating Direction Method of Multipli

researcharxiv-cs-lg

16 Apr 2026

Hybrid Approach for Enhancing Lesion Segmentation in Fundus Images

arXiv:2509.25549v2 Announce Type: replace Abstract: Choroidal nevi are common benign pigmented lesions in the eye, with a small risk of transforming into melanoma. Early detection is critical to impro

I defended my thesis today! Sincere thanks to my advisors @sainingxie @ylecun and committee members: @mengyer @YiMaTweets @LukeZettlemoyer @…

I defended my thesis today! Sincere thanks to my advisors @sainingxie @ylecun and committee members: @mengyer @YiMaTweets @LukeZettlemoyer @liuzhuang1234. I could not have wished for a better PhD life

researchyann-lecun--x

Identifiability of Potentially Degenerate Gaussian Mixture Models With Piecewise Affine Mixing

arXiv:2604.13218v1 Announce Type: cross Abstract: Causal representation learning (CRL) aims to identify the underlying latent variables from high-dimensional observations, even when variables are depe

Is carbon removal in trouble?

Last week, news outlets reported that Microsoft was pausing carbon removal purchases. It was something of a bombshell. The thing is, Microsoft is the carbon removal market. The company has single-hand

researchmit-tech-review

JD Vance is lecturing the Pope on Catholicism and Pierre Poilievre is lecturing Mark Carney on economics and RFK Jr is lecturing scientists …

JD Vance is lecturing the Pope on Catholicism and Pierre Poilievre is lecturing Mark Carney on economics and RFK Jr is lecturing scientists about vaccines and Donald Trump is lecturing the world on ta

researchyann-lecun--x

Just Use XML: Revisiting Joint Translation and Label Projection

arXiv:2603.12021v2 Announce Type: replace Abstract: Label projection is an effective technique for cross-lingual transfer, extending span-annotated datasets from a high-resource language to low-resour

Learning-Based Estimation of Spatially Resolved Scatter Radiation Fields in Interventional Radiology

arXiv:2512.17654v3 Announce Type: replace Abstract: We present three variants of a lightweight, fully connected artificial neural network, suited for interactive estimation of three-dimensional, spati

Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification

arXiv:2604.13546v1 Announce Type: new Abstract: Conventional neural networks strictly separate learning and inference because if parameters are updated during inference, outputs become unstable and ev

Learning Sewing Patterns via Latent Flow Matching of Implicit Fields

arXiv:2601.17740v2 Announce Type: replace Abstract: Sewing patterns define the structural foundation of garments and are essential for applications such as fashion design, fabrication, and physical si

LEGO-MOF: Equivariant Latent Manipulation for Editable, Generative, and Optimizable MOF Design

arXiv:2604.13520v1 Announce Type: new Abstract: Metal-organic frameworks (MOFs) are highly promising for carbon capture, yet navigating their vast design space remains challenging. Recent deep generat

Linear Probe Accuracy Scales with Model Size and Benefits from Multi-Layer Ensembling

arXiv:2604.13386v1 Announce Type: new Abstract: Linear probes can detect when language models produce outputs they 'know' are wrong, a capability relevant to both deception and reward hacking. However

MAGA has a Europe problem. Not the real Europe. The one they invented. The one with sharia courts and no-go zones and zero tech companies an…

MAGA has a Europe problem. Not the real Europe. The one they invented. The one with sharia courts and no-go zones and zero tech companies and miserable citizens begging for permission to cross the str

researchyann-lecun--x

Making AI operational in constrained public sector environments

The AI boom has hit across industries, and public sector organizations are facing pressure to accelerate adoption. At the same time, government institutions face distinct constraints around security,

researchmit-tech-review

Minimax Optimality and Spectral Routing for Majority-Vote Ensembles under Markov Dependence

arXiv:2604.13414v1 Announce Type: new Abstract: Majority-vote ensembles achieve variance reduction by averaging over diverse, approximately independent base learners. When training data exhibits Marko

Mitigating Barren Plateaus in Quantum Denoising Diffusion Probabilistic Model

arXiv:2512.06695v2 Announce Type: replace Abstract: Quantum generative models exploit quantum superposition and entanglement to enhance learning efficiency for both classical and quantum data. Recentl

mLaSDI: Multi-stage latent space dynamics identification

arXiv:2506.09207v4 Announce Type: replace Abstract: Accurately solving partial differential equations (PDEs) is essential across many scientific disciplines. However, high-fidelity solvers can be comp

Mobius transforms and Shapley values for vector-valued functions on weighted directed acyclic multigraphs

arXiv:2510.05786v3 Announce Type: replace-cross Abstract: Mobius inversion and Shapley values are two mathematical tools for characterizing and decomposing higher-order structure in complex systems. T

Momentum Further Constrains Sharpness at the Edge of Stochastic Stability

arXiv:2604.14108v1 Announce Type: new Abstract: Recent work suggests that (stochastic) gradient descent self-organizes near an instability boundary, shaping both optimization and the solutions found.

Monthly Diffusion v0.9: A Latent Diffusion Model for the First AI-MIP

arXiv:2604.13481v1 Announce Type: new Abstract: Here, we describe Monthly Diffusion at 1.5-degree grid spacing (MD-1.5 version 0.9), a climate emulator that leverages a spherical Fourier neural operat

Multi-modal panoramic 3D outdoor datasets for place categorization

arXiv:2604.13142v1 Announce Type: cross Abstract: We present two multi-modal panoramic 3D outdoor (MPO) datasets for semantic place categorization with six categories: forest, coast, residential area,

Multistage Conditional Compositional Optimization

arXiv:2604.14075v1 Announce Type: cross Abstract: We introduce Multistage Conditional Compositional Optimization (MCCO) as a new paradigm for decision-making under uncertainty that combines aspects of

Native Hybrid Attention for Efficient Sequence Modeling

arXiv:2510.07019v3 Announce Type: replace Abstract: Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recal

Neural 3D Reconstruction of Planetary Surfaces from Descent-Phase Wide-Angle Imagery

arXiv:2604.13235v1 Announce Type: new Abstract: Digital elevation modeling of planetary surfaces is essential for studying past and ongoing geological processes. Wide-angle imagery acquired during spa

Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models

arXiv:2601.11340v2 Announce Type: replace Abstract: Chain-of-Thought reasoning has significantly enhanced the problem-solving capabilities of Large Language Models. Unfortunately, current models gener

Neuromorphic Spiking Ring Attractor for Proprioceptive Joint-State Estimation

arXiv:2604.14021v1 Announce Type: new Abstract: Maintaining stable internal representations of continuous variables is fundamental for effective robotic control. Continuous attractor networks provide

researcharxiv-cs-ro

node2vec or triangle-biased random walks: stationarity, regularity & recurrence

arXiv:2604.13681v1 Announce Type: cross Abstract: The node2vec random walk is a non-Markovian random walk on the vertex set of a graph, widely used for network embedding and exploration. This random w

OmniTrace: A Unified Framework for Generation-Time Attribution in Omni-Modal LLMs

arXiv:2604.13073v1 Announce Type: new Abstract: Modern multimodal large language models (MLLMs) generate fluent responses from interleaved text, image, audio, and video inputs. However, identifying wh

On an L^2 norm for stationary ARMA processes

arXiv:2408.10610v5 Announce Type: replace Abstract: We propose an L^2 norm for stationary Autoregressive Moving Average (ARMA) models. We look at ARMA models within the Hilbert space of the past with

OneHOI: Unifying Human-Object Interaction Generation and Editing

arXiv:2604.14062v1 Announce Type: new Abstract: Human-Object Interaction (HOI) modelling captures how humans act upon and relate to objects, typically expressed as triplets. Existing approaches split

Outperforming Self-Attention Mechanisms in Solar Irradiance Forecasting via Physics-Guided Neural Networks

arXiv:2604.13455v1 Announce Type: new Abstract: Accurate Global Horizontal Irradiance (GHI) forecasting is critical for grid stability, particularly in arid regions characterized by rapid aerosol fluc

PAT-VCM: Plug-and-Play Auxiliary Tokens for Video Coding for Machines

arXiv:2604.13294v1 Announce Type: new Abstract: Existing video coding for machines is often trained for a specific downstream task and model. As a result, the compressed representation becomes tightly

Physically-Guided Optical Inversion Enable Non-Contact Side-Channel Attack on Isolated Screens

arXiv:2604.13419v1 Announce Type: new Abstract: Noncontact exfiltration of electronic screen content poses a security challenge, with side-channel incursions as the principal vector. We introduce an o

Physics-Informed Neural Networks for Methane Sorption: Cross-Gas Transfer Learning, Ensemble Collapse Under Physics Constraints, and Monte Carlo Dropout Uncertainty Quantification

arXiv:2604.13992v1 Announce Type: new Abstract: Accurate methane sorption prediction across heterogeneous coal ranks requires models that combine thermodynamic consistency, efficient knowledge transfe

Physics-Informed Neural Networks for Solving Derivative-Constrained PDEs

arXiv:2604.13723v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) recast PDE solving as an optimisation problem in function space by minimising a residual-based objective, yet m

Physics-informed reservoir characterization from bulk and extreme pressure events with a differentiable simulator

arXiv:2604.13291v1 Announce Type: new Abstract: Accurate characterization of subsurface heterogeneity is challenging but essential for applications such as reservoir pressure management, geothermal en

PRiMeFlow: Capturing Complex Expression Heterogeneity in Perturbation Response Modelling

arXiv:2604.13986v1 Announce Type: new Abstract: Predicting the effects of perturbations in-silico on cell state can identify drivers of cell behavior at scale and accelerate drug discovery. However, m

Provably Efficient Offline-to-Online Value Adaptation with General Function Approximation

arXiv:2604.13966v1 Announce Type: new Abstract: We study value adaptation in offline-to-online reinforcement learning under general function approximation. Starting from an imperfect offline pretraine

Quantifying and Understanding Uncertainty in Large Reasoning Models

arXiv:2604.13395v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have recently demonstrated significant improvements in complex reasoning. While quantifying generation uncertainty in LR

QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs

arXiv:2604.13786v1 Announce Type: new Abstract: As large language models become standard backends for content generation, practical provenance increasingly requires multi-bit watermarking. In provider

Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors

arXiv:2604.13951v1 Announce Type: new Abstract: This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analy

RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment

arXiv:2604.13492v1 Announce Type: cross Abstract: Radar is more resilient to adverse weather and lighting conditions than visual and Lidar simultaneous localization and mapping (SLAM). However, most r

Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport

arXiv:2604.13830v1 Announce Type: cross Abstract: Integro-differential equations arise in a wide range of applications, including transport, kinetic theory, radiative transfer, and multiphysics modeli

Reachability Constraints in Variational Quantum Circuits: Optimization within Polynomial Group Module

arXiv:2604.13735v1 Announce Type: cross Abstract: This work identifies a necessary condition for any variational quantum approach to reach the exact ground state. Briefly, the norms of the projections

Reconstruction of a 3D wireframe from a single line drawing via generative depth estimation

arXiv:2604.13549v1 Announce Type: new Abstract: The conversion of 2D freehand sketches into 3D models remains a pivotal challenge in computer vision, bridging the gap between human creativity and digi

ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks

arXiv:2603.28942v3 Announce Type: replace Abstract: The pervasive deployment of deep learning models across critical domains has concurrently intensified privacy concerns due to their inherent propens

Right Regions, Wrong Labels: Semantic Label Flips in Segmentation under Correlation Shift

arXiv:2604.13326v1 Announce Type: new Abstract: The robustness of machine learning models can be compromised by spurious correlations between non-causal features in the input data and target labels. A