Search: “research”

Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLA

arXiv:2610.05025v1 Announce Type: new Abstract: Dual-system Vision-Language-Action (VLA) models improve real-time robotic control by pairing a slow, reasoning-capable generalist with a fast specialist

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Trinity: One Differentiable Physics for Training, Refining and Scoring Generative Floorplanners

DGX agent

arXiv:2610.04957v1 Announce Type: new Abstract: Floorplanning arranges the blocks of a chip and decides their shapes under objectives that press blocks together, short wirelength and a small outline,

researcharxiv-cs-lg

6 Oct 2026

Trust the View That Sees the Target: Mining Cross-View Conflicts for Reliability-Gated Disaster Damage Assessment

arXiv:2610.04327v1 Announce Type: new Abstract: After a disaster, building damage is assessed from overhead tiles and ground-level photographs, and most methods fuse the two views symmetrically, trust

TSAE: Structured Sparse Autoencoders for Interpreting Time-Series Forecasting Models

arXiv:2610.04925v1 Announce Type: new Abstract: Time-series forecasting informs critical decisions in energy dispatch, industrial operations, and environmental monitoring; understanding the patterns m

Two Americas of Well-Being: Divergent Rural-Urban Patterns of Life Satisfaction and Happiness from 2.6 B Social Media Posts

arXiv:2511.10542v2 Announce Type: replace-cross Abstract: Using 2.6 billion geolocated social-media posts (2014-2022) and a fine-tuned generative language model, we construct county-level indicators o

Two-Point Local Optimality in k-Means via Boundary-Point Screening

arXiv:2610.06182v1 Announce Type: new Abstract: Lloyd's algorithm and the discrete local (D-local) optimization method (Li et al., 2025) for k-means provide only weak local-optimality guarantees, and

Underscoring the Problem: Why Softpick Fails at Initialization

arXiv:2610.05488v1 Announce Type: new Abstract: Softmax attention gives every token a nonzero weight, which in trained models concentrates into attention sinks and massive activations that widen the d

Understanding Certified Training with Interval Bound Propagation

arXiv:2306.10426v3 Announce Type: replace Abstract: As robustness verification methods are becoming more precise, training certifiably robust neural networks is becoming ever more relevant. To this en

Understanding Gap-Dependent Regret for Optimism-Based Reinforcement Learning with Linear Function Approximation

arXiv:2602.20297v2 Announce Type: replace-cross Abstract: We study gap-dependent regret for reinforcement learning with linear function approximation. While prior works have established gap-dependent

Understanding over-squashing and bottlenecks on graphs via curvature

arXiv:2111.14522v4 Announce Type: replace-cross Abstract: Most graph neural networks (GNNs) use the message passing paradigm, in which node features are propagated on the input graph. Recent works poi

Understanding the Weight Averaging Mechanism in LLM Training for Post-Training Quantization

arXiv:2610.05329v1 Announce Type: new Abstract: Large language models (LLMs) are typically pretrained in high precision but increasingly deployed with low-precision post-training quantization (PTQ). R

Universal Test-Time Training

arXiv:2610.05484v1 Announce Type: cross Abstract: Recent Test-Time Training (TTT) architectures compress context into fast weights that are updated online and queried as memory. Existing TTT designs k

Unmentioned Checklist Findings Change How Reinforcement Learning Appears to Improve Chest Radiograph Report Checking

arXiv:2610.05425v1 Announce Type: new Abstract: Automated checks of radiology reports may rely on AI-generated checklists that leave findings unmentioned. We used reinforcement learning to train a vis

VCURF: Virtual Camera-based Uncertainty of Radiance Fields

arXiv:2610.04076v1 Announce Type: new Abstract: Radiance fields, implemented with either implicit (NeRF) or explicit (Gaussian Splatting) representations, are advancing the state of the art in novel v

VICON: Visual-Inertial-Contact based Hand-Object Tracking for Manipulation Datasets

arXiv:2610.05180v1 Announce Type: new Abstract: Learning dexterous manipulation benefits from human demonstration datasets that capture diverse and natural hand-object interactions. In particular, con

VisualErase: Dual-Branch Visual Trajectory Redirection for Robust Concept Erasure in Text-to-Image Diffusion Models

arXiv:2610.05000v1 Announce Type: new Abstract: Concept erasure is essential for the safe deployment of text-to-image diffusion models, as they may reproduce harmful, copyrighted, or privacy-sensitive

VLA-ZO: Fast Zeroth-Order Adaptation for Vision-Language-Action Models

arXiv:2610.06271v1 Announce Type: new Abstract: Adapting vision-language-action (VLA) models to deployment-time distribution shifts is important for reliable robotic operation, but conventional first-

VolS-GS: Relightable Gaussian Splatting with Volumetric Subsurface Scattering

arXiv:2610.04007v1 Announce Type: new Abstract: We present VolS-GS, a relightable Gaussian splatting framework that reconstructs objects from one-light-at-a-time (OLAT) captures and renders them under

WaveGSSM: Graph Wave State Space Models for Propagating Spatio-Temporal Patterns

arXiv:2610.06540v1 Announce Type: new Abstract: Spatio-temporal graph models typically encode each snapshot with a GNN and then connect the resulting representations through a temporal module. This sp

What the Guard Misses, the Robot Executes: Implied Harm in VLA Instructions

arXiv:2610.05818v1 Announce Type: new Abstract: Vision-language-action models (VLAs) act on instructions without being able to refuse, so screening harmful requests falls to monitors. We test whether

When Are Concept Bottleneck Model Explanations Faithful and Compact?

arXiv:2610.06285v1 Announce Type: new Abstract: Concept bottleneck models (CBMs) are neural classifiers that allow to explain their decisions via high-level concepts, potentially enabling understandin

When Low Prediction Error Misleads Planning: Diagnosing Representation, Dynamics, and Decision Failures in Latent World Models

arXiv:2610.05550v1 Announce Type: new Abstract: The component that dominates a latent world model's prediction error need not be the one whose repair most improves action selection. We show this by co

When the noncommutative AM-GM inequality holds

arXiv:2610.04874v1 Announce Type: cross Abstract: In this note, we prove that the noncommutative AM-GM inequality holds if nge 2lceil m/2 rceil^2. The motivation comes from counterexamples constructed

Where Does Jagged Competence Come From?

arXiv:2610.03831v1 Announce Type: new Abstract: Capable systems often show jagged competence: low average error alongside failures on particular inputs. We ask where it comes from in a task built from

Where Does the Semantic Gain Come From? A Reproduction and Extension of Semantic Knowledge-driven Contrastive Learning for Long-Tailed Recognition

arXiv:2610.04104v1 Announce Type: new Abstract: Semantic Knowledge-driven Contrastive Learning (SKCL) uses a language model to decide which classes are related, and pulls each image towards the protot

You May Be Running the Wrong Inception Crop

arXiv:2610.04147v1 Announce Type: new Abstract: A decade after its inception, Inception crop has become the standard crop-based data augmentation method for training deep vision models. Not only is it

Your Temporal Link Predictor Is Blind to Who Is Active: A Missing Factor That Transfers Across Models

arXiv:2610.04869v1 Announce Type: new Abstract: An interaction has two parts: someone decides to act, and then chooses whom to act on. Temporal link prediction has concentrated on the second, and we s

Your Unlearning Gives You Away: Identifying Erased Concepts in Diffusion Models

arXiv:2610.05601v1 Announce Type: new Abstract: Existing attacks on unlearned diffusion models assume that the erased concepts are known in advance and focus on recovering them. In practice, however,

A Composable AI-Accelerated Iterative Solver for 3D-IC Thermal Modeling

arXiv:2610.02461v1 Announce Type: new Abstract: Accurate thermal analysis of heterogeneous 2.5D/3D-IC packages is essential yet computationally prohibitive. A single full-package FEM simulation can ta

A Fully Automatic Pipeline for 3D Dendrite Instance Segmentation in SBF-SEM

arXiv:2610.03332v1 Announce Type: new Abstract: Accurate three-dimensional (3D) reconstruction of individual dendrites in serial block-face scanning electron microscopy (SBF-SEM) is essential for quan

A generative-informed neuro-symbolic framework for syntactic ambiguity resolution: Evidence from Arabic DPs

arXiv:2610.02529v1 Announce Type: new Abstract: Syntactic ambiguity poses a persistent challenge for Arabic NLP, particularly in morphologically rich nominal constructions where multiple structu6ral i

researcharxiv-cs-cl

A hybrid CNN-adjoint optimization framework for reconstruction of viscoelastic tissue properties in magnetic resonance elastography

arXiv:2610.02634v1 Announce Type: cross Abstract: Magnetic resonance elastography (MRE) is a noninvasive imaging modality for quantifying the viscoelastic properties of soft tissues from shear wave pr

A Missing Latent, Not a Missing Simulator: Radius-Augmented Inference for Real JWST Retrieval

arXiv:2610.02245v1 Announce Type: cross Abstract: Amortized simulation-based inference (SBI), which is trained on radiative-transfer simulators, recovers exoplanet atmospheres accurately on synthetic

A Multi Method Importance and Performance Efficiency Analysis of Topological Metrics for Natural Visibility Graph Based Cyber Attack Detection

arXiv:2610.02342v1 Announce Type: new Abstract: Natural Visibility Graph (NVG) based analysis characterizes network traffic through topological descriptors reflecting different structural properties.

A Passive AI System for Verifying Physical State on Automated Liquid Handlers

arXiv:2610.02668v1 Announce Type: new Abstract: Automated liquid handlers execute digital protocols, but operators must assemble the deck and confirm that the physical setup matches the intended exper

A Sobel-Gradient MLP Baseline for Handwritten Character Recognition

arXiv:2508.11902v4 Announce Type: replace Abstract: This study examines how much handwritten-character information is retained by a deliberately simple first-order edge representation. Instead of lear

A Two-Stage Cascade for Near-Real-Time Forest Anomaly Detection from Sentinel-1 SAR Time Series

arXiv:2610.02763v1 Announce Type: new Abstract: Tropical forest monitoring is essential for global climate stability and biodiversity preservation. To address the urgent need for rapid, reliable detec

Accurate Open-Loop Control of a Soft Continuum Robot Using Visually Learned Latent Dynamics

arXiv:2603.19655v2 Announce Type: replace Abstract: This work addresses open-loop control of a soft continuum robot (SCR) from video-learned latent dynamics. Visual Oscillator Networks (VONs) from pre

Adaptive Second-Order Solvers for Fast Stochastic Diffusion Sampling

arXiv:2610.03034v1 Announce Type: cross Abstract: Diffusion models rely on numerical solvers requiring time-discretization, which has a large influence on the tradeoff between sampling cost and qualit

researcharxiv-cs-cl

AIBL: Augmented Instance-Based Learning with Structured Memory and Neural Embeddings

arXiv:2610.03413v1 Announce Type: new Abstract: Sequential learning systems often make decisions from accumulated experience while receiving high-dimensional inputs whose distribution may change over

AMBER: Multi-View Adaptive Budget Allocation for Listwise Vision-Language Reranking

arXiv:2610.02831v1 Announce Type: new Abstract: Vision-language models (VLMs) are powerful listwise rerankers for multimodal retrieval, but high inference costs restrict them to evaluating small local

Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models

arXiv:2610.03647v1 Announce Type: cross Abstract: Many machine learning methods aim to approximate the lower-dimensional manifold on which the data lives. A desirable feature of such methods is that t

An AI-Based Multi-Stage Approach for Androgenetic Alopecia Assessment from Low-Magnification Scalp Images

arXiv:2610.02421v1 Announce Type: new Abstract: Androgenetic alopecia (AGA) is characterized by patterned follicular miniaturization, increased single-hair follicular units, and altered hair-shaft dia

ANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling

arXiv:2602.09009v2 Announce Type: replace-cross Abstract: Scaling network depth has been a central driver behind the success of modern foundation models, yet recent investigations suggest that deep la

Answering clinicians' questions over trial evidence tables with verifiable, feedback-driven language models

arXiv:2610.02576v1 Announce Type: new Abstract: Systematic reviews condense clinical trials into evidence tables, yet clinicians can interrogate these tables only through database queries, and many qu

Approximation Property of Dropout Neural Networks: Sobolev Rates and Confidence Bounds

arXiv:2610.02253v1 Announce Type: new Abstract: The universal approximation property of dropout neural networks does not by itself describe the network size required for an accurate random realization

AREX: Affine-Residual Exponential Integrator for Few-Step Sampling in Flow Matching

arXiv:2610.03483v1 Announce Type: cross Abstract: We introduce AREX, a training-free sampler for pretrained flow matching models that uses the target mean and covariance to capture an analytically tra

Asymptotic Performance of Time-Varying Bayesian Optimization

arXiv:2505.13012v3 Announce Type: replace-cross Abstract: Time-Varying Bayesian Optimization (TVBO) is the go-to framework for optimizing a time-varying black-box objective function that may be noisy