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Failure-Resilient Multi-Robot Coordination with k-Connectivity Constrained Submodular Maximization

arXiv:2610.13049v1 Announce Type: new Abstract: Multi-robot coordination is essential in applications such as coverage, target tracking, and information gathering, where robots must jointly select act

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Faithfulness Without Anchors: A Position Paper on the Structural Misalignments of Explainable AI Faithfulness Metrics for Feature Importance

DGX agent

arXiv:2610.12493v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) tools have often been presented as methods to increase trust in machine learning models by making aspects of t

researcharxiv-cs-ai

12 Oct 2026

FallGown: A Soft Pneumatic Wearable Device for Fall Prevention

arXiv:2610.12706v1 Announce Type: new Abstract: Concerns about falling and potential resulting injuries prevent many older adults from participating in forms of health-improving exercise such as walki

Fear Is Not Always Fear: Variation in Emotion Label Equivalence Across Datasets

arXiv:2610.12841v1 Announce Type: new Abstract: Emotion classifiers are routinely applied beyond their training data, on the assumption that same-named labels such as fear or surprise mean the same th

Finite-Sample Guarantees for Fully Discrete Conditional Diffusion Models

arXiv:2610.13851v1 Announce Type: cross Abstract: We establish finite-sample guarantees for conditional diffusion models learned from data and implemented with finitely many denoising steps. Our appro

Forecasting Corpus-Sampling Disagreement in Masked Text Reconstruction

arXiv:2610.12987v1 Announce Type: new Abstract: If a second text corpus were collected from the same population, how much would a predictor's outputs change? We study this question for masked-text rec

From Imbalance to Evidence: Deep Nonparametric Testing for Complex Data under Severe Sample Imbalance

arXiv:2610.12946v1 Announce Type: cross Abstract: Comparing distributions under severe sample imbalance requires effectively using abundant majority observations while retaining sensitivity to differe

From Impact to Insight: Dynamics-Aware Proprioceptive Terrain Sensing on Granular Media

arXiv:2604.02563v2 Announce Type: replace Abstract: Robots that traverse natural terrain must interpret contact forces generated under highly dynamic conditions. However, most terrain characterization

From Structure to Validity: Mechanism-Guided Generation and Refinement of LLM Rubrics

arXiv:2610.13375v1 Announce Type: new Abstract: Rubrics have been widely used to evaluate and optimize language models on open-ended tasks. However, existing work primarily focuses on generating bette

Gaussian-Width Bounds for Offline-to-Online Linear Bandits

arXiv:2610.12990v1 Announce Type: new Abstract: We study how offline data can help online learning in stochastic linear bandits. We focus on partially covered offline data, where only k of the d featu

Generalized Determinantal Point Processes for Attraction and Repulsion with Distinct Interaction Kernels

arXiv:2610.12894v1 Announce Type: cross Abstract: Determinantal point processes (DPPs) model subset selection probability with repulsion, but many applications also exhibit attraction arising from pai

Geometry-Aware Multi-Objective Optimization: Norm-Constrained Oracles with Entropic Weight Updates

arXiv:2610.13773v1 Announce Type: cross Abstract: Multiple-gradient descent is typically formulated in Euclidean geometry, whereas matrix-aware optimizers use directions induced by other norms. We ana

GIST: Generator-state-Informed Supervision for Tabular Foundation Models

arXiv:2610.12904v1 Announce Type: new Abstract: Tabular foundation models (TFMs) based on prior-data fitted networks typically use sampled hard query labels, leaving avoidable sampling variability in

GlucoPRISM: Protocol-Supervised Pretraining for Cross-Cohort Glucose Transfer

arXiv:2610.12528v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) foundation models encode each day as one vector that mixes who the person is, what happened that day and how the sen

Golden Anchor for Video Generation

arXiv:2610.13217v1 Announce Type: cross Abstract: Video generation supports digital content creation, with applications in virtual avatars, AI-driven filmmaking, interactive game engines, and world mo

Graph-Based Heuristics for Minimum Constraint Removal in Cluttered Robot Motion Planning

arXiv:2610.12609v1 Announce Type: new Abstract: Humanoid and service robots operating in clut- tered human environments may encounter motion planning problems that are infeasible when all surrounding

Harmonic analysis and circuit approximation of Sobolev functions on quantum input spaces

arXiv:2610.13477v1 Announce Type: cross Abstract: We derive approximation rates for Sobolev functions defined on the complex unit sphere and complex projective space, representing quantum states, and

Heterogeneity-Aware Client Sampling for Optimal and Efficient Federated Learning

arXiv:2505.11304v4 Announce Type: replace-cross Abstract: Federated learning (FL) commonly involves clients with diverse communication and computational capabilities. Such heterogeneity can significan

How Reliable are AMR Parser Outputs? Uncertainty Estimation for AMR Parsing

arXiv:2610.13236v1 Announce Type: cross Abstract: Recent advances have significantly improved the performance of Abstract Meaning Representation (AMR) parsers, yet determining when their outputs can b

How Well Do Prior-Data Fitted Networks Amortize Bayesian Inference?

arXiv:2610.13764v1 Announce Type: cross Abstract: Prior-data fitted networks (PFNs) are trained to approximate the Bayesian posterior predictive distribution (PPD) of a synthetic prior, yet results ab

Image-Based Path-Planning for Navigation of Soft-Growing Robots in the Spinal Sub-Arachnoid Space

arXiv:2610.12631v1 Announce Type: new Abstract: Recently, soft robotic procedures are being developed aiming at achieving targeted minimally invasive operations or drug administration in specific loca

Instance-Level Difficulty: A Missing Perspective in Machine Unlearning

arXiv:2410.03043v3 Announce Type: replace Abstract: Current research on deep machine unlearning primarily focuses on improving or evaluating the overall effectiveness of unlearning methods while overl

JEPA-kMMVAE: CSI Prediction for Time-Varying Wireless Channels

arXiv:2610.13315v1 Announce Type: cross Abstract: This paper considers channel state information (CSI) prediction using neural networks for time-varying multi-antenna channels from noisy historical ob

Kairos: Toward a Byte-Level Foundation Model for Every Modality

arXiv:2610.12495v1 Announce Type: cross Abstract: Small language models trained on a single local machine leave little room for architectural trial and error. Kairos combines bidirectional gated-Delta

KL Before and After Mixing: A Round-Complexity Separation in Parallel Sampling

arXiv:2610.13924v1 Announce Type: new Abstract: A parallel sampler can choose at random which coordinates to generate together. For a target p and the output law q_U of a schedule U drawn afresh for e

Kronecker Product Attention: Memory-Efficient KV Compression via Structured Factorization

arXiv:2610.12657v1 Announce Type: cross Abstract: Efficient autoregressive generation is increasingly limited by the memory footprint of the key-value (KV) cache, which grows linearly with sequence le

KV-Repurpose: A Testbed for Evaluating Non-Prefix KV-Cache Reuse

arXiv:2610.13060v1 Announce Type: new Abstract: KV-cache reuse in large language model serving is commonly limited to exact prompt prefixes, preventing reuse when the same retrieved document appears a

Learning by Compression: Risk Estimates Attain the Law-of-Large-Numbers Rate

arXiv:2610.13442v1 Announce Type: cross Abstract: Compression schemes provide a general framework for deriving data-dependent risk bounds for learning algorithms. For learning rules based on preferent

Learning More by Training Less: Uncertainty-Guided Progressive Contraction for Efficient Reasoning Post-Training

arXiv:2610.12933v1 Announce Type: new Abstract: Large language models have achieved remarkable advances in complex reasoning. However, scaling reasoning post-training with ever-larger corpora can subs

Learning Size Independent Constraint Models from Input Data and Positive and Negative Example Solutions

arXiv:2610.13640v1 Announce Type: new Abstract: In this paper we describe a Constraint Acquisition Tool that generates size independent constraint programs from input data and positive and negative ex

Lesion-DDPM: Lesion-Enhanced 3D Diffusion for MS MRI Synthesis

arXiv:2606.15457v2 Announce Type: replace-cross Abstract: 3D FLAIR MRI is widely recommended as one of the standard MRI sequences for brain imaging in multiple sclerosis (MS), but publicly available M

Linearized Wasserstein dimensionality reduction with approximation guarantees

arXiv:2302.07373v2 Announce Type: replace Abstract: We introduce LOT Wassmap, a computationally feasible algorithm to uncover low-dimensional structures in the Wasserstein space. The algorithm is moti

Locally Private Parametric Methods for Change-Point Detection

arXiv:2602.13619v2 Announce Type: replace-cross Abstract: We study parametric change-point detection under local differential privacy, focusing on the offline localization of a single change point in

Looking Ahead and Back: Anticipatory Generative Modeling for Road-Network Trajectories

arXiv:2610.13131v1 Announce Type: new Abstract: Trajectory generation underpins urban applications such as traffic management and urban planning. Within road networks, vehicle movement along road segm

Looped Diffusion Transformer: the same blocks run several times inside each denoising step, and loop depth can be changed at sampling time [R]

researchr-machinelearning

Paper: Looped Diffusion Transformer (arXiv 2609.40305, 30 Sep). Instead of making a text-to-image DiT bigger, it runs a shared group of transformer blocks several times inside each denoising step. The

Lower Bounds for Randomized Linear-Oracle Optimization over Strongly Convex Sets

arXiv:2610.13590v1 Announce Type: cross Abstract: Recent results [arXiv:2602.04378, arXiv:2602.22608] have established worst-case objective-error lower bounds of order 1/T^2 after T linear minimizatio

Measuring Artifact Reliance in Machine-Generated Text Detectors

arXiv:2610.13583v1 Announce Type: new Abstract: Detectors of machine-generated text score almost perfectly on scientific-literature benchmarks, implying we can reliably distinguish with these detector

Mesh-Native Tokenisation: Retrofitting Foundation Models to Unstructured Data

arXiv:2610.12618v1 Announce Type: cross Abstract: Physics foundation models are an increasingly popular approach for building versatile emulators for spatiotemporal systems. They require tokenisation

MHR-Router: Multimodal Heterogeneous Retrieval-Enhanced Adaptive Routing for VLM Inference

arXiv:2610.13278v1 Announce Type: new Abstract: Vision-language models (VLMs) exhibit complementary capabilities, yet selecting the most suitable expert for a given image-question query remains challe

Minimax Rates for Estimating Powered Sliced Wasserstein Functionals

arXiv:2610.12740v1 Announce Type: cross Abstract: We study the two-sample estimation of the powered Sliced Wasserstein functional under projected r-th moment assumptions. Let N=nwedge m, where n and m

Model-agnostic Knowledge Augmented Machine Learning for Weakly Annotated Bioimaging Data

arXiv:2610.13637v1 Announce Type: cross Abstract: Machine learning models are increasingly used for automated feature extraction from weakly annotated bioimaging data, such as microscopy and cytomorph

Model-free Bayesian Clustering and Multimodal Posterior Summarisation

arXiv:2610.13397v1 Announce Type: cross Abstract: We develop a model-free, noise-aware Bayesian clustering framework that constructs a martingale posterior over clusterings from a predictive Bayesian

Monarch-MoE: Structured Experts for Multimodal Continual Instruction Tuning

arXiv:2610.13215v1 Announce Type: new Abstract: Learning new tasks in multimodal continual instruction tuning can cause catastrophic forgetting of previously acquired knowledge. Although multi-expert

Multi-Stream Attention Residuals

arXiv:2610.13630v1 Announce Type: new Abstract: Attention Residuals (AttnRes) enables content-dependent retrieval over network depth, which can be viewed as single-stream softmax attention along the d

Multidimensional Bayesian Active Machine Learning of Working Memory Task Performance

arXiv:2510.00375v3 Announce Type: replace Abstract: While adaptive experimental design has outgrown one-dimensional, staircase-based adaptations, most cognitive experiments still control a single fact

Multimodal Image-based Robotic Assistance and Guidance Environment (MIRAGE): A Novel Unified Framework for Surgical Navigation and Visualization

arXiv:2610.12780v1 Announce Type: new Abstract: This paper presents the computational architecture and quantitative preclinical evaluation of MIRAGE, a multimodal image-guided robotic surgery framewor

Neural expectation-maximization and meta-models

arXiv:2610.12741v1 Announce Type: new Abstract: We interpret Transformer networks as learned approximations to a hybrid probabilistic-inference procedure that combines max-product Loopy Belief Propaga

Neural networks are more modular than single neurons suggest

arXiv:2610.12842v1 Announce Type: new Abstract: Neural networks routinely develop representations in which individual neurons contribute to multiple distinct functions, leading to the widespread view