Search: “papers”

When Both Layers Learn: Training Dynamics of Representing Linear Models via ReLU Networks

arXiv:2606.04476v1 Announce Type: new Abstract: In this paper, we study the gradient descent dynamics for jointly training both layers of a one-hidden-layer ReLU network to fit a linear target functio

safetyarxiv-cs-lg

4 Jun 2026

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A Benchmark for Semi-supervised Multi-modal Crowd Counting

DGX agent

arXiv:2606.03646v1 Announce Type: new Abstract: This paper constructs the first benchmark on semi-supervised multi-modal crowd counting. To lay the foundation for this unexplored task, we first formul

model-releasesarxiv-cs-cv

3 Jun 2026

A formal definition and meta-model for a machine theory of mind

arXiv:2606.03471v1 Announce Type: new Abstract: This paper proposes, for the first time, a rigorous formal definition of the concept of Machine Theory of Mind, based on principles supported by evidenc

A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model

arXiv:2505.07068v2 Announce Type: replace-cross Abstract: In this paper, we investigate the data-driven identification of asymmetric interaction kernels in the Motsch-Tadmor model based on observed tr

Applying Two-Grid Preconditioner for Subsurface Flow Simulation using Attention-enhanced Hybrid Network to Accelerate Multiscale Discretization in High-contrast Media

arXiv:2606.02582v1 Announce Type: cross Abstract: In this paper, we study the efficient numerical solution of Darcy equations in strongly heterogeneous media with high-contrast permeability and propos

Autonomous Navigation System for Library Service Robot Based on Unitree Go2 Edu

arXiv:2606.03340v1 Announce Type: new Abstract: Libraries require autonomous robots to move quietly through narrow aisles while remaining safe around readers, chairs, bags, and carts. This paper prese

agentsarxiv-cs-ro

Decentralized Stochastic Nonconvex Optimization under the (L_0,L_1)-Smoothness

arXiv:2509.08726v3 Announce Type: replace-cross Abstract: This paper focuses on the decentralized stochastic optimization problem f(mathbf{x})=frac{1}{m}sum_{i=1}^m f_i(mathbf{x}) over a connected net

agentsarxiv-cs-lg

DeMuon: A Decentralized Muon for Matrix Optimization over Graphs

arXiv:2510.01377v2 Announce Type: replace-cross Abstract: In this paper, we propose DeMuon, a method for decentralized matrix optimization over a given communication topology. DeMuon incorporates matr

Exploring Easy Boosts for Lidar Semantic Scene Completion

arXiv:2606.03992v1 Announce Type: new Abstract: This paper investigates 'free lunch' strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectura

Fixed-Time Dynamic Landing of Quadrotors using Adaptive Unscented Kalman Filtering and Nonlinear Model Predictive Control

arXiv:2606.02658v1 Announce Type: new Abstract: This paper introduces an estimation and control framework for dynamic landing of multi-rotor uncrewed aerial vehicles on moving platforms. The proposed

From Control Boundary to Insurance Claim: Reconstructing AI-Mediated Losses Through the CER Framework

arXiv:2606.03777v1 Announce Type: new Abstract: AI losses that arise through an insured organization's generative or agentic AI system require state reconstruction, not merely event reconstruction, be

agentsarxiv-cs-ai

From None to All: Self-Supervised 3D Reconstruction via Novel View Synthesis

arXiv:2603.27455v2 Announce Type: replace Abstract: In this paper, we introduce NAS3R, a self-supervised feed-forward framework that jointly learns explicit 3D geometry and camera parameters with no g

Geometric Adaptive Control for a Quadrotor UAV with Wind Disturbance Rejection

arXiv:1803.06363v2 Announce Type: cross Abstract: This paper presents a geometric adaptive control scheme for a quadrotor unmanned aerial vehicle, where the effects of unknown, unstructured disturbanc

Geometric Adaptive Control with Neural Networks for a Quadrotor UAV in Wind fields

arXiv:1903.02091v1 Announce Type: cross Abstract: This paper proposes a geometric adaptive controller for a quadrotor unmanned aerial vehicle with artificial neural networks. It is assumed that the dy

Applications

High-Dimensional Latents Should Be Diagnosed Through Phase Structure

arXiv:2606.02600v1 Announce Type: cross Abstract: We study autoencoder and variational-autoencoder latent spaces through the lens of spin-glass theory. The paper has two components. First, we formaliz

applicationsarxiv-cs-lg

Hybrid Dynamics Modeling for a Flexible 2-DoF Robotic Arm

model-releasesarxiv-cs-ro

arXiv:2606.02969v1 Announce Type: new Abstract: This paper examines three approaches for modeling the dynamics of a flexible-link 2-DoF robotic arm to address unmodeled dynamics not captured by rigid-

Inverting the Generation Process of Denoising Diffusion Implicit Models: Empirical Evaluation and a Novel Method

arXiv:2606.03111v1 Announce Type: new Abstract: This paper studies the problem of inverting the DDIM image generation process to recover latent variables, particularly the initial noise map, from a ge

Leveraging BART to Assess CS1 C++ Programming Assignments using Rubric-based Criteria

arXiv:2606.03814v1 Announce Type: new Abstract: This paper investigates rubric-aware, multitask fine-tuning of transformer models for automated grading of introductory C++ programming assignments, wit

safetyarxiv-cs-ai

Lingo_Research_Group at SemEval-2026 Task 9: Evaluating Prompt Variants for Polarization Detection

arXiv:2606.03334v1 Announce Type: new Abstract: Our submission presented in this paper is for SemEval-2026 Task 9: Multilingual Text Classification Challenge - Polarization Detection and it covers all

researcharxiv-cs-cl

On dynamic multi-agent pathfinding methods: review, simulations and modifications

arXiv:2606.03735v1 Announce Type: cross Abstract: This paper presents a systematic study of pathfinding algorithms in the context of Dynamic Multi-Agent Pathfinding (D-MAPF), a setting that combines d

agentsarxiv-cs-ro

Online Learning with Gradient-Variation Interval Regret

arXiv:2606.03831v1 Announce Type: new Abstract: This paper investigates non-stationary online learning using the metric of interval regret, which requires an online algorithm to perform well over ever

OpenAgenet/OAN: Technical Architecture for Trust-Governed Agent Identity and Discovery

arXiv:2606.03163v1 Announce Type: cross Abstract: This paper describes the technical architecture of OpenAgenet / OAN. OAN is a protocol-neutral trust layer for open Agent interconnection. It specifie

agentsarxiv-cs-ai

R2DN: Scalable Parameterization of Contracting and Lipschitz Recurrent Deep Networks

arXiv:2504.01250v2 Announce Type: replace Abstract: This paper presents the Robust Recurrent Deep Network (R2DN), a scalable parameterization of robust recurrent neural networks for machine learning a

R^{2k} is Theoretically Large Enough for Embedding-based Top-k Retrieval

arXiv:2601.20844v3 Announce Type: replace-cross Abstract: This paper studies the Minimal Embeddable Dimension (MED): the least dimension in which there exists a configuration of m object vectors so th

Rethinking Neural Width for Alternating Current Optimal Power Flow Proxies

arXiv:2606.03125v1 Announce Type: new Abstract: Deep learning proxies for Alternating Current Optimal Power Flow (ACOPF) lack systematic methods for determining architectural size. This paper conducts

safetyarxiv-cs-lg

Spike-Aware C++ INT8 Inference for Sparse Spiking Language Models on Commodity CPUs

arXiv:2606.03026v1 Announce Type: cross Abstract: Spiking language models expose activation sparsity that dense Transformer runtimes do not directly exploit. This paper studies that property from a sy

Static and Dynamic Representations for Tactile Contact-Angle Estimation with Event-Based Sensors

arXiv:2606.03545v1 Announce Type: new Abstract: Event-based tactile sensing offers low-latency signal acquisition for contact-rich robotic interaction. This paper investigates contact-angle estimation

Terminal Time and Angle-Constrained Nonlinear Intercept Guidance

arXiv:2606.02872v1 Announce Type: cross Abstract: This paper considers the problem of simultaneously controlling an interceptor's impact time and impact angle using its lateral acceleration as the sol

The next chapter in flood resilience: Open sourcing Google’s hydrology framework

Google has open-sourced its flood forecasting framework, which replicates operational FloodHub model training settings and reflects methodology described in a 2024 Nature paper for global ungauged flo

researchgoogle-research

WaterSIC: Information-Theoretically (Near) Optimal Linear Layer Quantization

model-releasesarxiv-cs-lg

arXiv:2603.04956v2 Announce Type: replace Abstract: This paper considers the problem of converting a given dense linear layer to low precision. The tradeoff between compressed length and output discre

Wavelet as Tokenizer: Preliminary Results on a Shared Wavelet Token Schema for Natural Signals

arXiv:2606.02631v1 Announce Type: cross Abstract: This paper studies whether audio, images, and video can share a common wavelet token schema rather than relying on separate modality-specific latent g

3rd Place at CVPR 2026 CASTLE Challenge: Agentic Multi-View Long-Context Video Understanding via Hierarchical Knowledge Graph Retrieval

model-releasesarxiv-cs-cv

arXiv:2606.01933v1 Announce Type: new Abstract: This paper presents our winning methodology for the CASTLE 2026 Challenge at the CVPR 2026 EgoVis Workshop, where our team secured third place globally.

A Minimalist Brain-Computer Musical Interface for Real-Time Emotion-Driven Sonification: System Design and Preliminary Evaluation

arXiv:2606.01473v1 Announce Type: new Abstract: This paper presents a minimalist brain-computer Musical Interface (BCMI) that functions as a real-time affective sonification system, translating prefro

Application of Algorithms in Energy-Efficient Design Platforms for Green Building

arXiv:2606.01229v1 Announce Type: new Abstract: During green building design, computer-aided energy assessment is widely used to improve efficiency and achieve overall optimization. This paper present

agentsarxiv-cs-ai

ASE-26: a curriculum for agentic software engineering as a discipline

arXiv:2606.01152v1 Announce Type: cross Abstract: The work of a professional software engineer has begun to consist, increasingly, of directing agents rather than writing code, and the empirical evide

Local Ai

Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control

arXiv:2606.00737v1 Announce Type: new Abstract: This paper investigates the optimization mechanisms of non-convex Model Predictive Control (MPC) using the Maximum Entropy Differential Dynamic Programm

local-aiarxiv-cs-ro

Cognitive-Linguistic Indicators of Depression in Online Communities: Analysed by DistilBERT and Holographic Reduced Representation

arXiv:2606.00026v1 Announce Type: new Abstract: This paper investigates whether combining cognitively grounded linguistic features with transformer-based embeddings improves automated detection of dep

researcharxiv-cs-cl

Consistency evaluation of benchmarks used for causal discovery

arXiv:2606.01789v1 Announce Type: new Abstract: In graphical causal model, causal discovery aims to construct a causal graph based on numerical data and domain knowledge in plain text. However, the ev

Applications

Discovering Nonlinear Static Relationships in Unlabeled Dataset using Autoencoder with Ordered Variance

arXiv:2402.14031v2 Announce Type: replace-cross Abstract: This paper presents an autoencoder with ordered variance (AEO), in which the conventional reconstruction loss is augmented by a variance-based

applicationsarxiv-cs-lg

Dynamic Entropy Tuning in Reinforcement Learning Low-Level Quadcopter Control: Stochasticity vs Determinism

arXiv:2512.18336v2 Announce Type: replace-cross Abstract: This paper explores the impact of dynamic entropy tuning in Reinforcement Learning (RL) algorithms that train a stochastic policy. Its perform

safetyarxiv-cs-ai

Echo State Networks for Time Series Forecasting: Hyperparameter Sweep and Benchmarking

model-releasesarxiv-cs-lg

arXiv:2602.03912v4 Announce Type: replace Abstract: This paper investigates the performance of Echo State Networks (ESNs) for univariate forecasting of monthly and quarterly time series from the M4 Fo

Edge Prediction for Roof Wireframe Reconstruction with Transformers

arXiv:2606.02406v1 Announce Type: new Abstract: This paper presents a competitive solution to the S23DR Challenge 2026, which aims to reconstruct 3D house roof wireframe models from sparse SfM point c

Encoded but Not Routed: Explaining the Table-Chart Gap in Scientific Claim Verification

arXiv:2606.01679v1 Announce Type: new Abstract: Multimodal LLMs are increasingly used to assist scientific peer review, where a core requirement is verifying whether claims in a paper are supported by

researcharxiv-cs-cl

FlatVPR: Plug-and-play Geo-linear Residual Adapter for Geometric Rectification of Foundation Model Feature Manifolds

arXiv:2606.01734v1 Announce Type: new Abstract: This paper proposes ``FlatVPR,'' a novel geometric rectification paradigm that effectively bridges the trade-off between map lightweightness and localiz

Generalization of Gibbs and Langevin Monte Carlo Algorithms in the Interpolation Regime

arXiv:2510.06028v3 Announce Type: replace Abstract: This paper provides data-dependent bounds on the expected error of the Gibbs algorithm in the overparameterized interpolation regime, where low trai

How Accurately Can a Gaussian Approximate Stochastic Approximation Iterates?

arXiv:2602.13906v2 Announce Type: replace-cross Abstract: Stochastic approximation (SA) is a method for finding the root of an operator perturbed by noise. The focus of this paper is studying the dist

HumanNOVA: Photorealistic, Universal and Rapid 3D Human Avatar Modeling from a Single Image

arXiv:2606.02573v1 Announce Type: new Abstract: In this paper, we present HumanNOVA, a photorealistic, universal, and rapid model for generating 3D human avatars from a single RGB image. Achieving bot

Implicit Regularization for Multi-label Feature Selection

arXiv:2411.11436v2 Announce Type: replace-cross Abstract: In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit