Search: “models”

Causal Learning with Neural Assemblies

arXiv:2604.26919v1 Announce Type: cross Abstract: Can Neural Assemblies -- groups of neurons that fire together and strengthen through co-activation -- learn the direction of causal influence between

tutorialsarxiv-cs-ai

Circular Phase Representation and Geometry-Aware Optimization for Ptychographic Image Reconstruction

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DGX agent

arXiv:2604.26664v1 Announce Type: cross Abstract: Traditional iterative reconstruction methods are accurate but computationally expensive, limiting their use in high-throughput and real-time ptychogra

researcharxiv-cs-cv

30 Apr 2026

Classification of Public Opinion on the Free Nutritional Meal Program on YouTube Media Using the LSTM Method

arXiv:2604.26312v1 Announce Type: new Abstract: Public opinion towards the Free Nutritious Meal Program (MBG) on YouTube social media reflects diverse community responses. This study applies the Long

safetyarxiv-cs-cl

CoFL: Continuous Flow Fields for Language-Conditioned Navigation

arXiv:2603.02854v2 Announce Type: replace-cross Abstract: Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--

local-aiarxiv-cs-ai

COMMA: Coordinate-aware Modulated Mamba Network for 3D Dispersed Vessel Segmentation

arXiv:2503.02332v3 Announce Type: replace-cross Abstract: Accurate segmentation of 3D vascular structures is essential for various medical imaging applications. The dispersed nature of vascular struct

Deep Agents is all you need https://github.com/langchain-ai/deepagents

Deep Agents is a framework or library developed by LangChain that enables the creation of sophisticated AI agents with enhanced reasoning capabilities. The project likely provides tools and abstractio

agentsharrison-chase--x

DiffAnon: Diffusion-based Prosody Control for Voice Anonymization

arXiv:2604.26281v1 Announce Type: cross Abstract: To preserve or not to preserve prosody is a central question in voice anonymization. Prosody conveys meaning and affect, yet is tightly coupled with s

Differentially-Private Text Rewriting reshapes Linguistic Style

arXiv:2604.26656v1 Announce Type: new Abstract: Differential Privacy (DP) for text matured from disjointed word-level substitutions to contiguous sentence-level rewriting by leveraging the generative

researcharxiv-cs-cl

Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields

arXiv:2604.26095v1 Announce Type: new Abstract: {Closed-loop inverse source localization and characterization (ISLC) requires a mobile agent to select measurements that localize sources and infer late

local-aiarxiv-cs-ai

Applications

DP-CDA: An Algorithm for Enhanced Privacy Preservation in Dataset Synthesis Through Randomized Mixing

arXiv:2411.16121v3 Announce Type: replace-cross Abstract: In recent years, the growth of data across various sectors, including healthcare, security, finance, and education, has created significant op

applicationsarxiv-cs-lg

EnerGS: Energy-Based Gaussian Splatting with Partial Geometric Priors

arXiv:2604.26238v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has been widely adopted for scene reconstruction, where training inherently constitutes a highly coupled and non-convex opt

Evaluating Strategic Reasoning in Forecasting Agents

arXiv:2604.26106v1 Announce Type: new Abstract: Forecasting benchmarks produce accuracy leaderboards but little insight into why some forecasters are more accurate than others. We introduce Bench to t

Explainable Representation of Finite-Memory Policies for POMDPs using Decision Trees

arXiv:2411.13365v2 Announce Type: replace Abstract: Partially Observable Markov Decision Processes (POMDPs) are a fundamental framework for decision-making under uncertainty and partial observability.

tutorialsarxiv-cs-ai

Factorizable joint shift revisited

arXiv:2601.15036v3 Announce Type: replace Abstract: Factorizable joint shift (FJS) represents a type of distribution shift (or dataset shift) that comprises both covariate and label shift. Recently, i

Failure Modes of Maximum Entropy RLHF

arXiv:2509.20265v3 Announce Type: replace-cross Abstract: In this paper, we show that Simple Preference Optimization (SimPO) can be derived as Maximum Entropy Reinforcement Learning, providing a theor

researcharxiv-cs-cl

FalconApp: Rapid iPhone Deployment of End-to-End Perception via Automatically Labeled Synthetic Data

arXiv:2604.25949v1 Announce Type: new Abstract: Reliable perception for robotics depends on large-scale labeled data, yet real-world datasets rely on heavy manual annotation and are time-consuming to

local-aiarxiv-cs-ro

FASH-iCNN: Making Editorial Fashion Identity Inspectable Through Multimodal CNN Probing

arXiv:2604.26186v1 Announce Type: new Abstract: Fashion AI systems routinely encode the aesthetic logic of specific houses, editors, and historical moments without disclosing it. We present FASH-iCNN,

Federated Medical Image Classification under Class and Domain Imbalance exploiting Synthetic Sample Generation

arXiv:2604.26324v1 Announce Type: new Abstract: Exploiting deep learning in medical imaging faces critical challenges, including strict privacy constraints, heterogeneous imaging devices with varying

Fireside chat at Sequoia Ascent 2026 from a ~week ago. Some highlights: The first theme I tried to push on is that LLMs are about a lot more…

Fireside chat at Sequoia Ascent 2026 from a ~week ago. Some highlights: The first theme I tried to push on is that LLMs are about a lot more than just speeding up what existed before (e.g. coding). Th

agentskarpathy--x

Generalized Disguise Makeup Presentation Attack Detection Using an Attention-Guided Patch-Based Framework

arXiv:2604.26025v1 Announce Type: new Abstract: Despite significant advances in facial recognition systems, they remain vulnerable to face presentation attacks. Among them, disguise makeup attacks are

tutorialsarxiv-cs-cv

Geometric Inverse Flight Dynamics on SO(3) and Application to Tethered Fixed-Wing Aircraft

arXiv:2602.17166v2 Announce Type: replace Abstract: We present a robotics-oriented, coordinate-free formulation of inverse flight dynamics for fixed-wing aircraft on SO(3). Translational force balance

researcharxiv-cs-ro

Google Cloud is rebuilding the enterprise stack for the age of agents

Google Cloud is assembling an ambitious agentic enterprise stack it believes will close the gap between AI ambition and real business outcomes. But the transition from traditional, linear workflows to

agentssiliconangle

Graph Construction and Matching for Imperative Programs using Neural and Structural Methods

arXiv:2604.26578v1 Announce Type: cross Abstract: Reusing verification artefacts requires identifying structural and semantic similarities across programs and their specifications. In this paper, we f

researcharxiv-cs-ai

Grounding vs. Compositionality: On the Non-Complementarity of Reasoning in Neuro-Symbolic Systems

arXiv:2604.26521v1 Announce Type: new Abstract: Compositional generalization remains a foundational weakness of modern neural networks, limiting their robustness and applicability in domains requiring

researcharxiv-cs-ai

Heterogeneous Adaptive Policy Optimization: Tailoring Optimization to Every Token's Nature

arXiv:2509.16591v2 Announce Type: replace Abstract: Using entropy as a measure of heterogeneity to guide optimization has emerged as a crucial research direction in Reinforcement Learning for LLMs. Ho

safetyarxiv-cs-cl

Incorporating Expert Knowledge into Bayesian Causal Discovery of Mixtures of Directed Acyclic Graphs

arXiv:2510.06735v2 Announce Type: replace Abstract: Bayesian causal discovery benefits from prior information elicited from domain experts, and in heterogeneous domains any prior knowledge would be ba

Laplace Approximation for Bayesian Tensor Network Kernel Machines

arXiv:2604.26673v1 Announce Type: cross Abstract: Uncertainty estimation is essential for robust decision-making in the presence of ambiguous or out-of-distribution inputs. Gaussian Processes (GPs) ar

Learning Vision-Based Omnidirectional Navigation: A Teacher-Student Approach Using Monocular Depth Estimation

arXiv:2603.01999v2 Announce Type: replace-cross Abstract: Reliable obstacle avoidance in industrial settings demands 3D scene understanding, but widely used 2D LiDAR sensors perceive only a single hor

safetyarxiv-cs-cv

Majority of this work and awesome eval was done by @MehulKalia_ ! We're hiring an EM and a senior IC for this team :) Want to join him? appl…

Majority of this work and awesome eval was done by @MehulKalia_ ! We're hiring an EM and a senior IC for this team :) Want to join him? apply at http://www.notion.com/careers When we evaluated agentic

agentslinus-lee--x

Mapping the maturation of TCM as an adjuvant to radiotherapy

arXiv:2601.11923v2 Announce Type: replace Abstract: The integration of complementary medicine into oncology represents a paradigm shift that has seen to increasing adoption of Traditional Chinese Medi

safetyarxiv-cs-cl

MedSynapse-V: Bridging Visual Perception and Clinical Intuition via Latent Memory Evolution

arXiv:2604.26283v1 Announce Type: cross Abstract: High-precision medical diagnosis relies not only on static imaging features but also on the implicit diagnostic memory experts instantly invoke during

MemOVCD: Training-Free Open-Vocabulary Change Detection via Cross-Temporal Memory Reasoning and Global-Local Adaptive Rectification

arXiv:2604.26774v1 Announce Type: cross Abstract: Open-vocabulary change detection aims to identify semantic changes in bi-temporal remote sensing images without predefined categories. Recent methods

researcharxiv-cs-ai

Mini-Batch Class Composition Bias in Link Prediction

arXiv:2604.25978v1 Announce Type: cross Abstract: Prior work on node classification has shown that Graph Neural Networks (GNNs) can learn representations that transfer across graphs, when underlying g

Mining Negative Sequential Patterns to Improve Viral Genomic Feature Representation and Classification

arXiv:2604.25968v1 Announce Type: cross Abstract: Viruses represent the most abundant biological entities on Earth and play a pivotal role in microbial ecosystems, yet, as prominent human pathogens, t

MTCurv: Deep learning for direct microtubule curvature mapping in noisy fluorescence microscopy images

arXiv:2604.26517v1 Announce Type: new Abstract: Accurate quantification of the geometry of curvilinear biological structures is essential for understanding cellular mechanics and disease-related morph

Multiple Consistent 2D-3D Mappings for Robust Zero-Shot 3D Visual Grounding

arXiv:2604.26261v1 Announce Type: new Abstract: Zero-shot 3D Visual Grounding (3DVG) is a critical capability for open-world embodied AI. However, existing methods are fundamentally bottlenecked by th

local-aiarxiv-cs-cv

NeuralEmu: in situ Measurement-Driven, ML-based, High-Fidelity 5G Network Emulation

arXiv:2604.26080v1 Announce Type: cross Abstract: Current and future applications demand ultra-low latency and consistent throughput, yet frequently traverse 5G cellular networks, so cope with volatil

NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data

arXiv:2602.03169v2 Announce Type: replace-cross Abstract: Clustering functional data in the presence of phase variation is challenging, as temporal misalignment can obscure intrinsic shape differences

Obliviator Reveals the Cost of Nonlinear Guardedness in Concept Erasure

arXiv:2603.07529v2 Announce Type: replace Abstract: Concept erasure aims to remove unwanted attributes, such as social or demographic factors, from learned representations, while preserving their task

tutorialsarxiv-cs-lg

Order-Sensitive Sequential Interventions on Ideal Lattices

arXiv:2604.26472v1 Announce Type: cross Abstract: We study sequential interventions under prerequisite constraints. In this setting, admissible intervention sequences are paths in the ideal lattice of

local-aiarxiv-cs-lg

OT Score: An OT based Confidence Score for Prototype-Assisted Source Free Unsupervised Domain Adaptation

arXiv:2505.11669v3 Announce Type: replace-cross Abstract: We address the computational and theoretical limitations of current distributional alignment methods for source-free unsupervised domain adapt

Point Cloud Registration via Probabilistic Self-Update Local Correspondence and Line Vector Sets

arXiv:2604.26318v1 Announce Type: new Abstract: Point cloud registration (PCR) is a fundamental task for integrating 3D observations in remote sensing applications. This paper proposes a fast and effe

local-aiarxiv-cs-cv

Industry

Predicting Readmissions Isn't Enough. Acting in Time Is.

This article emphasizes that healthcare organizations must move beyond simply predicting hospital readmissions to taking timely preventive actions based on those predictions. It likely discusses how m

industrydatabricks

Applications

Qvine: Vine Structured Quantum Circuits for Loading High Dimensional Distributions

arXiv:2604.26213v1 Announce Type: cross Abstract: Loading high dimensional distributions is an important task for utilizing quantum computers on applications ranging from machine learning to finance.

applicationsarxiv-cs-ai

RE-MCDF: Closed-Loop Multi-Expert LLM Reasoning for Knowledge-Grounded Clinical Diagnosis

arXiv:2602.01297v3 Announce Type: replace Abstract: Electronic medical records (EMRs), particularly in neurology, are inherently heterogeneous, sparse, and noisy, which poses significant challenges fo

agentsarxiv-cs-ai

Reactive Motion Generation via Phase-varying Neural Potential Functions

arXiv:2604.26450v1 Announce Type: new Abstract: Dynamical systems (DS) methods for Learning-from-Demonstration (LfD) provide stable, continuous policies from few demonstrations. First-order dynamical

researcharxiv-cs-ro

Recipes for Calibration Checks in Safety-Critical Applications

arXiv:2604.26479v1 Announce Type: cross Abstract: Safety-critical prediction systems, such as autonomous vehicles, weather forecasters, and medical monitors, commonly rely on probabilistic forecasters

safetyarxiv-cs-lg

Recurrence-Based Nonlinear Vocal Dynamics as Digital Biomarkers for Depression Detection from Conversational Speech

arXiv:2604.26242v1 Announce Type: cross Abstract: Digital biomarkers for depression have largely relied on static acoustic descriptors, pooled summary statistics, or conventional machine learning repr