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Modeling Deletion Requests in Machine Unlearning

arXiv:2610.04310v1 Announce Type: new Abstract: Machine unlearning is seen as a promising approach to enable users to exercise the 'right to erasure' in the context of AI models. We ask how users migh

Applications

MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation

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DGX agent

arXiv:2503.09950v2 Announce Type: replace Abstract: In this paper, we address the problem of human trajectory forecasting, which aims to predict the inherently multi-modal future movements of humans b

applicationsarxiv-cs-cv

6 Oct 2026

Moment-Accurate Gaussian Mixtures for Constant-Step Stochastic Approximation

arXiv:2610.05595v1 Announce Type: cross Abstract: Local Gaussian models of constant-step learning predict output variability and expected losses, but weak convergence alone does not justify these mome

local-aiarxiv-cs-lg

Monitorability Disposition in Large Reasoning Models

arXiv:2610.04914v1 Announce Type: cross Abstract: Monitoring the chain-of-thought (CoT) of large reasoning models (LRMs) is a common way to detect misbehavior in real-world practice. However, current

Monocular markerless biomechanics for clinically interpretable gait assessment in spinal cord injury

arXiv:2610.05552v1 Announce Type: new Abstract: Three-dimensional gait analysis guides rehabilitation after spinal cord injury but depends on marker-based motion capture and force plates, which few cl

MOSAIC-SV: Real-Time Adaptive Identification of Vessel Dynamics for the Control and Deployment of Aquatic Robots

arXiv:2610.03898v1 Announce Type: new Abstract: Model-based control of an aquatic robotic platform depends on a hydrodynamic model that is costly to identify and specific to the hull, payload, and con

Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph

arXiv:2411.12426v3 Announce Type: replace Abstract: Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based

MOXIE: Discovering Alternative Explanations for Biomedical Image Classifiers

arXiv:2610.04814v1 Announce Type: new Abstract: Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from one fixed image segmentation. This hides t

MTOR: Generalizable AI-Generated Video Detection with Multimodal Semantics and Temporal Over-Regularity

arXiv:2610.06378v1 Announce Type: new Abstract: The rapid evolution of video generation has narrowed the perceptual gap between authentic and synthetic videos, making generalizable AI-generated video

MTRACE: Multilingual Retrieval-Augmented Generation for Temporally Diverse Text Corpora

arXiv:2512.12694v2 Announce Type: replace-cross Abstract: Large multilingual knowledge bases expose temporally diverse information, yet retrieval quality remains sensitive to lexical variation and cro

MTV: Revisiting Multi-Task Visual Representation Learning

arXiv:2601.13886v2 Announce Type: replace Abstract: Current visual representation learning remains bifurcated: vision-language models (e.g., CLIP) excel at global semantic alignment but lack spatial p

local-aiarxiv-cs-cv

Mulligan: Performance-Guided Data Collection for Efficient On-Robot Learning

arXiv:2610.05882v1 Announce Type: cross Abstract: Learning from human demonstrations is a reliable way to teach robots new tasks, but the gains from each additional demonstration shrink as the policy

Multi-Agent Spectrum Sharing

model-releasesarxiv-cs-lg

arXiv:2610.04802v1 Announce Type: new Abstract: This project explores how multiple cognitive radars can learn to share limited wireless spectrum with other radio users without interfering with one ano

Multi-Crop Leaf Disease Recognition: A Unified Benchmark and Cross-Region Study

arXiv:2610.04456v1 Announce Type: new Abstract: Deep learning models for crop leaf disease recognition routinely report near-perfect accuracy yet are typically trained and evaluated on a single datase

Applications

Multi-Marginal Schrodinger Bridge Matching

arXiv:2510.16587v2 Announce Type: replace-cross Abstract: Understanding the continuous evolution of populations from discrete temporal snapshots is a critical research challenge, particularly in field

applicationsarxiv-cs-lg

Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data

arXiv:2610.06389v1 Announce Type: new Abstract: Super-resolution and semantic segmentation are known to benefit one another, especially in the Earth observation context. However, learning both tasks i

MultiLoc: Look Around As You Localize for Fast And Robust Visual Re-localization

arXiv:2603.27170v2 Announce Type: replace Abstract: Relative camera pose is a basic geometric cue for visual re-localization and scene understanding. When using images alone, visual evidence may not s

Applications

Multimodal Deep Survival Analysis for Sinkhole Susceptibility

arXiv:2610.06365v1 Announce Type: new Abstract: Sinkholes are a widespread geohazard in karst terrain. In Florida, soluble carbonate bedrock, shallow groundwater, and intense rainfall combine to make

applicationsarxiv-cs-lg

Multitask Conditional Generative Adversarial Network Enables Automatic Whole Knee Cartilage and Menisci Segmentation and Reliable T1r{ho} and T2 Quantification Without High-Resolution Morphological Images

arXiv:2610.06602v1 Announce Type: new Abstract: Early osteoarthritis detection through quantitative MRI (qMRI) requires accurate cartilage and meniscus segmentation, traditionally necessitating time-c

MuViSeg: Multi-View Segment Correspondences from Dense Geometry Priors

arXiv:2607.17938v2 Announce Type: replace Abstract: Object-level mapping and topological navigation reason about whole objects, yet the correspondences they rely on are computed over keypoints or pixe

NAMVIS: Next-Scale Autoregressive Multi-View Image Synthesis

arXiv:2610.04722v1 Announce Type: new Abstract: Sparse-view novel view synthesis is a central problem in 3D content creation, but diffusion-based approaches remain limited by iterative denoising, maki

Near-Optimal Complexity of Finite-Sum Nonconvex-Strongly-Concave Minimax Optimization

arXiv:2610.04944v1 Announce Type: cross Abstract: We characterize, up to logarithmic factors, the minimax expected query complexity of finite-sum nonconvex-strongly-concave optimization under mean-squ

Neural Barriers: An Online Certifiable Learning-enhanced Adaptive High Order Safety Critical Control

arXiv:2610.05542v1 Announce Type: new Abstract: Control barrier functions are an effective model-based tool to formally certify the safety of a system. However, transferring their theoretical guarante

safetyarxiv-cs-ro

Tutorials

Neural Bayesian Filtering

arXiv:2510.03614v2 Announce Type: replace Abstract: Sequential estimation under partial observability requires tracking beliefs that may be high-dimensional, multimodal, and non-Gaussian. Classical Ba

tutorialsarxiv-cs-lg

NeuroCBIR: A Fast and Accurate Image Retrieval System for Whole-Brain and Region-Specific MRI

arXiv:2610.06502v1 Announce Type: new Abstract: Content-based image retrieval (CBIR) in neuroimaging enables the identification of structurally similar brain scans, supporting diagnosis, prognosis, an

NM-LIO: Multiple LiDAR-Inertial Odometry Addressing LiDAR Measurement Noise Discrepancy

arXiv:2610.04551v1 Announce Type: new Abstract: Multiple LiDAR-inertial odometry methods have been widely applied in robotic applications owing to their enhanced accuracy and reliability. However, ado

No Concept Escapes the Audit: Auditing-Aware Unlearning for Verifiable Concept Erasure in Diffusion Models

arXiv:2610.05401v1 Announce Type: new Abstract: Text-to-image diffusion models can generate prohibited content, which motivates concept erasure through machine unlearning. Most erasure methods interve

local-aiarxiv-cs-lg

Non-invasive Seizure Detection Using Wearable Wrist-worn Accelerometry and Deep Learning

arXiv:2610.05919v1 Announce Type: new Abstract: Seizure monitoring and detection are crucial for reducing the morbidity and mortality associated with seizures. Current epilepsy care, often involving e

Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

arXiv:2610.04545v1 Announce Type: cross Abstract: This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributi

local-aiarxiv-cs-ro

Now You Feel It, Now You See Me: Digital-Twin-based Teleoperation Interface for Dexterous Manipulation

arXiv:2610.05081v1 Announce Type: new Abstract: Teleoperation is becoming increasingly important for collecting high-quality demonstrations to teach robots dexterous manipulation skills. For dexterous

Nudge Before You Push: Physics-Aware Navigation via Tactile Probing

arXiv:2610.04924v1 Announce Type: new Abstract: Visually identical containers can conceal loads that require different handling decisions. We present TANav, which uses a brief nudge to measure push re

Occlusion-Aware Contingency Safety-Critical Planning for Autonomous Driving

arXiv:2502.06359v3 Announce Type: replace Abstract: Ensuring safe driving while maintaining travel efficiency for autonomous vehicles in dynamic and occluded environments is a critical challenge. This

safetyarxiv-cs-ro

OccStress: Stress-Testing the 4D Occupancy Forecasting Chain

arXiv:2512.15621v2 Announce Type: replace Abstract: Occupancy world models use historical occupancy states to forecast future 3D scenes, but their robustness under corrupted temporal inputs remains po

Tutorials

OCL-PDE: A Generative Framework for PDE Inverse Problems with Observation-Complementary Latents

arXiv:2610.06259v1 Announce Type: new Abstract: Partial differential equation (PDE) inverse problems are often ill-posed, making fine-scale details difficult to recover. We address this problem by int

tutorialsarxiv-cs-lg

Tutorials

OctMesh: A Unified Octree-Hierarchical Framework for Lossless Triangle Mesh Compression

arXiv:2610.04281v1 Announce Type: new Abstract: Lossless triangle mesh compression must preserve both vertex positions and connectivity. Octrees support learned point cloud geometry coding and progres

tutorialsarxiv-cs-cv

Odyssey: A Closed-Loop Benchmark for Long-Horizon Real-World Driving with Explicit Navigation Routes

model-releasesarxiv-cs-ro

arXiv:2610.06469v1 Announce Type: new Abstract: Closed-loop evaluation of end-to-end driving requires continuous rollouts that reveal how earlier decisions affect subsequent driving. However, existing

Off-Policy Merging Beats On-Policy Self-Distillation for Continual Learning

arXiv:2610.05872v1 Announce Type: new Abstract: A long-standing goal of AI is a model that can continually learn and improve itself. On post-trained models, supervised finetuning (SFT) on new data oft

OGAM: Connecting Systematic Testing to Runtime Assurance through Object-Grounded Attention Monitoring for VLA Policies

model-releasesarxiv-cs-lg

arXiv:2610.05878v1 Announce Type: new Abstract: Benchmarks expose vision-language-action (VLA) policies to few canonical instructions, while exhaustive deployment testing is impossible. We introduce O

On architectural choices for interpretability and thermodynamic consistency in Physically Recurrent Neural Networks in the low-data regime

arXiv:2610.04067v1 Announce Type: new Abstract: In this paper, we unravel the effect of different decoder architectures on the interpretability of the latent space of the Physically Recurrent Neural N

On Hyperparameter Tuning on the Test Set

arXiv:2610.05902v1 Announce Type: cross Abstract: 'Don't tune hyperparameters on the test set' is often stated in machine learning textbooks. Violating it is considered a cardinal sin that produces mi

On Impact of Loss Function on the Performance of Neural Networks in Melanoma Diagnosis

arXiv:2610.06139v1 Announce Type: cross Abstract: Melanoma is the deadliest type of skin cancer, whose early diagnosis is crucial for patients' survival. Image classification using deep learning model

Agents

On Learning Optimal Corners in Orthogonal Partially Observable Cooperative Guard Art Galleries

arXiv:2610.06777v1 Announce Type: cross Abstract: The CADENCE algorithm solves the Partially Observable Cooperative Guard Art Gallery Problem (POCGAGP) with formal coverage and connectivity guarantees

agentsarxiv-cs-lg

On prediction from expert advice with more than five experts

arXiv:2610.05186v1 Announce Type: cross Abstract: We prove that no single rank ordered adversary strategy is globally optimal for the prediction with expert advice problem with six or more experts, in

On Semi-Markov Suboptimality in Hierarchical Reinforcement Learning

arXiv:2610.05338v1 Announce Type: new Abstract: Hierarchical reinforcement learning uses temporally extended subtasks for exploration, yet committing to their execution can restrict both deployment an

On the Approximation Relationship between Optimizing Ratio of Submodular (RS) and Difference of Submodular (DS) Functions

arXiv:2101.01631v2 Announce Type: cross Abstract: We demonstrate that from an algorithm guaranteeing an approximation factor for the ratio of submodular (RS) optimization problem, we can build another

On the Cardinality of Optimal Representations in the Binary-Source Information Bottleneck

arXiv:2610.06627v1 Announce Type: cross Abstract: The information bottleneck (IB) seeks a representation U of a source X that retains as much information as possible about a target Y, subject to a con

On the Geometry of Multimodal Saturation: Riemannian VICReg

arXiv:2610.06096v1 Announce Type: new Abstract: In self-supervised learning, a third modality should improve, or at least preserve, performance. Across nine image-text-tabular datasets, we show that i

On the Trade-off Between Information Loss and Generalization in Sparse Attention

model-releasesarxiv-cs-lg

arXiv:2610.04424v1 Announce Type: new Abstract: To mitigate the quadratic complexity bottleneck of the Transformer, sparse attention has emerged as a pivotal technology. Despite the extensive empirica