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VGGT-CAD: Reconstructing Parametric CAD 3D Model with Geometric Grounding

arXiv:2609.21225v1 Announce Type: new Abstract: Parametric CAD reconstruction requires recovering both precise geometry and editable modeling operations from visual observations, making it challenging

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Human DGX agent

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Research

VideoReloc: Long-Term Indoor Video Relocalization against a Kilobyte-Scale Semantic Scene Graph

DGX agent

arXiv:2609.21804v1 Announce Type: new Abstract: Given a compact semantic scene graph, long-term indoor video relocalization estimates a map-frame trajectory after lighting and furniture changes. Visua

researcharxiv-cs-cv

21 Sept 2026

VidOmni-Bench: A Benchmark for Fine-Grained Video Understanding via Spatio-Temporal Event Verification across Complexity and Duration

model-releasesarxiv-cs-ai

arXiv:2609.21521v1 Announce Type: cross Abstract: While Video Large Language Models (Video-LLMs) have recently demonstrated strong performance, reliably evaluating their fine-grained video understandi

VIRGA: Virtual-Agent-Intermediated Riemannian Geometry for Active-Sensing Air-Ground Coordination

arXiv:2609.21883v1 Announce Type: new Abstract: Air-ground autonomy becomes harder when the unmanned aerial vehicle (UAV) must remain observable by a gimbal light detection and ranging (LiDAR) mounted

safetyarxiv-cs-ro

VISPATH: Visual-Intent-Guided Path Reasoning for Multimodal Knowledge Graph Question Answering

model-releasesarxiv-cs-cl

arXiv:2609.20843v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) enables models to answer natural-language questions through structured graph reasoning and has achieved substa

Visual Navigation Transformer with Pose Attention

arXiv:2609.21212v1 Announce Type: cross Abstract: Learned navigation policies typically consume observations as a temporally ordered history, with positional encodings tying each observation to when i

Visual Proactivity: Enhancing Human-Robot Collaboration Through Intent Communication

arXiv:2609.21729v1 Announce Type: new Abstract: As robots transition from performing repetitive tasks to collaborating with humans, understanding human intent becomes crucial to effective interaction.

safetyarxiv-cs-ro

VLA-Scope: Shift-Aware Failure Prediction for Vision-Language-Action Models

arXiv:2609.21246v1 Announce Type: cross Abstract: Vision-language-action (VLA) models map visual observations and natural-language instructions to robotic actions, but distribution shifts can compromi

Voice-Light: A Full-Duplex Cascaded Voice Agent with Causal Turn-Taking and Speculative Generation

arXiv:2609.20995v1 Announce Type: cross Abstract: Natural spoken interaction requires more than streaming ASR, language generation, and speech synthesis: a system must react to overlap without canceli

safetyarxiv-cs-cl

Hardware

VoxelTTO: Voxel-Aligned Feed-Forward 3D Gaussian Splatting with Test-Time Optimization

arXiv:2609.21498v1 Announce Type: new Abstract: Recent feed-forward 3D Gaussian Splatting (3DGS) methods typically regress pixel-aligned Gaussian primitives, often causing excessive overlap and artifa

hardwarearxiv-cs-cv

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits

model-releasesarxiv-cs-cl

arXiv:2505.10202v2 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved remarkable success but face significant computational and memory challenges, particularly due to their ex

Watermarkable Multi-Draft Speculative Sampling via Poisson Processes

arXiv:2609.21858v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved state-of-the-art performance across a wide range of tasks, motivating two important aspects of deployment:

Weighted Quantum Signal Processing: Low-Depth Polynomial Approximation with Applications to Kolmogorov-Arnold Networks

model-releasesarxiv-cs-lg

arXiv:2609.21567v1 Announce Type: cross Abstract: Quantum Signal Processing is a powerful quantum framework for generating and approximating univariate polynomials. However, QSP is often limited by ci

What Must Survive? Exact Task-Information--State Frontiers for Resource-Sufficient Learning

arXiv:2609.21523v1 Announce Type: new Abstract: A system may be compressed before its downstream task is fully known. We ask how much retained state is then necessary and how much can be saved by limi

What Should We Ask Next? Retrieval-Aware Question Learning under Partial Evidence

arXiv:2609.21924v1 Announce Type: new Abstract: Interactive retrieval under partial evidence is a sequential information-acquisition problem: an agent must decide which question will create the most u

safetyarxiv-cs-ai

When AI Reviews Train AI Reviewers: Scientific-Judgment Collapse and Mitigation

model-releasesarxiv-cs-lg

arXiv:2609.20942v1 Announce Type: new Abstract: Large language models (LLMs) increasingly participate in scientific evaluation, both as automated reviewers and as assistants to human reviewers. As mod

When Better Turns Do Not Make Better Agents: Diagnosing the Gap Between Next-Turn Metrics and Workflow Success

model-releasesarxiv-cs-cl

arXiv:2609.21187v1 Announce Type: new Abstract: Agent models are frequently evaluated one decision at a time, where the model predicts the next action based on the gold interaction history, which is s

When Does Reasoning Help in Machine Translation? A Hierarchical Analysis of LRM Reasoning Traces

arXiv:2609.21247v1 Announce Type: new Abstract: Large Reasoning Models increasingly use intermediate traces for machine translation, but it remains unclear when such reasoning helps or hurts. We analy

researcharxiv-cs-cl

When Online Adaptation Hurts: Parameter-Frozen Test-Time Ensembling for Continual Medical Image Segmentation

arXiv:2609.21412v1 Announce Type: new Abstract: Medical image segmenters often get worse when sites, scanner vendors, or protocols change. Continual test-time adaptation (CTTA) addresses this problem

When Should a Failing Robot Ask? Initiating Corrective Human-Robot Dialogue from Audited Sensor Evidence

model-releasesarxiv-cs-ai

arXiv:2609.21942v1 Announce Type: cross Abstract: A robot that fails at a task faces the first decision in corrective dialogue: act on its own diagnosis, consult another onboard sensor, or interrupt a

Tutorials

When Should Robots Intervene? Balancing Engagement and Intrusiveness in Human-Robot Interaction

arXiv:2609.21734v1 Announce Type: new Abstract: Designing effective Human-Robot Interaction in task-oriented settings requires carefully balancing user engagement with socially acceptable levels of ro

tutorialsarxiv-cs-ro

When Steering Fails in Latent Reasoning: A Latent-to-Language Transition Gap

arXiv:2609.21662v1 Announce Type: cross Abstract: Activation steering has become a widely used approach for controlling language models during explicit chain-of-thought (CoT) reasoning, motivating its

When to Waddle: A Comparative Study of Bipedal Torso-Stabilization on Low-Friction Surfaces

arXiv:2609.21185v1 Announce Type: new Abstract: Low-friction surfaces challenge bipedal locomotion by limiting the contact forces available during stepping. Inspired by penguin waddling, we investigat

researcharxiv-cs-ro

WM-VS: Progress-Aligned World Models for Closed-Loop Visual Servoing

arXiv:2609.20892v1 Announce Type: cross Abstract: Closed-loop visual servoing requires predictions that indicate whether an action reduces task error, not only whether the action is plausible. We call

Local Ai

World Modeling in Transformers

arXiv:2609.21748v1 Announce Type: new Abstract: Behavioral failures can make a transformer appear to lack a world model even when it has learned faithful representations of its environment. We demonst

local-aiarxiv-cs-ai

Applications

WS-NeRF: A Mamba-Driven World-State-Aware Adaptive Deblurring Neural Radiance Field

arXiv:2609.21391v1 Announce Type: cross Abstract: Neural Radiance Fields (NeRF) have attracted extensive attention in recent years due to their strong capability for high-quality 3D reconstruction and

applicationsarxiv-cs-ai

XCalib Depth-Guided Geometric Optimization for Dense Thermal-Visible Video Registration

arXiv:2609.21770v1 Announce Type: new Abstract: Image registration is a vital preprocessing step in multimodal perception tasks, including image fusion, object detection, and semantic segmentation. In

safetyarxiv-cs-cv

ZeroTouch: Tactile-Supervised Visual Contact Estimation for Contact-Rich Manipulation

arXiv:2609.21726v1 Announce Type: new Abstract: Reliable robotic grasping benefits from estimating the evolving physical interaction and selecting a grasp-dependent compression target. Tactile sensors

researcharxiv-cs-ro

ZYT-World: A Real-Time Controllable World Model for Closed-Loop Autonomous-Driving Simulation

arXiv:2609.21712v1 Announce Type: new Abstract: Generative world models offer controllable and repeatable closed-loop simulation for end-to-end and vision-language-action driving policies, but product

Agents

4D Radar Perception Algorithms for Autonomous Driving: A Review

arXiv:2609.19216v1 Announce Type: cross Abstract: Research on 4D millimeter-wave radar perception algorithms has flourished in recent years, extending from signal processing and object detection to se

agentsarxiv-cs-cv

A Computational Tropical Geometry Framework for Neural Networks

arXiv:2405.20174v3 Announce Type: replace Abstract: We propose a computational tropical geometry framework for the symbolic analysis of neural networks with tropical activations. The number of linear

A Cross-Lingual Acoustic Disease-Alignment Framework for Respiratory Health Assessment from Spontaneous Speech

arXiv:2609.19398v1 Announce Type: cross Abstract: Spontaneous speech offers a scalable, noninvasive signal for respiratory health assessment, yet interpretable models that generalize across languages

safetyarxiv-cs-cl

Agents

A Dual-Process Perspective on Nudge Susceptibility in LLM-Based GUI Agents

arXiv:2609.19843v1 Announce Type: new Abstract: LLM-based GUI agents increasingly act on behalf of users in digital environments that were designed with human users in mind. These graphical user inter

agentsarxiv-cs-ai

A Dual-Stream Regulated Reconstruction and Segmentation Network with Hierarchical Artifact-Prior Modeling for Ultra-Low-Field Pediatric Neuroimaging

arXiv:2609.20562v1 Announce Type: new Abstract: Automated quality assessment, enhancement, and segmentation of multiple structures in 0.064,T ultra-low-field pediatric MRI are limited by a low signal-

researcharxiv-cs-cv

A Free Lunch? Adapting PP-OCRv6 for Historical Text Recognition

arXiv:2609.20064v1 Announce Type: new Abstract: Despite impressive reported scores, large vision-language models have seen limited practical uptake in historical automatic text recognition because of

researcharxiv-cs-cv

Agents

A frontend-backend architecture for tool calls in full-duplex speech models

arXiv:2609.19334v1 Announce Type: new Abstract: Full-duplex speech-to-speech (S2S) models provide natural, low-latency conversational interaction and would benefit from the ability to use external too

agentsarxiv-cs-cl

Applications

A Functional Pilot for Certified Freshness-Aware Semantic--Spatial Range Retrieval

arXiv:2609.19855v1 Announce Type: cross Abstract: Geographic applications need every object inside a radius that satisfies a semantic threshold, yet embedding indexes return approximate top-ranked lis

applicationsarxiv-cs-ai

A Generative-AI Modeling Framework for Explainable Decision Support in Complex Geosteering Scenarios

arXiv:2503.08509v2 Announce Type: replace Abstract: The real-time process of directional changes while drilling, known as geosteering, is crucial for hydrocarbon extraction and emerging directional dr

Applications

A Hybrid Gaze-Motor Imagery BCI Framework for Effective Decision Communication

arXiv:2609.20273v1 Announce Type: cross Abstract: Non-invasive brain-computer interfaces (BCIs) and eye-tracking technologies offer promising communication pathways; however, motor imagery (MI)-based

applicationsarxiv-cs-ai

A Large-Scale Vision-Language Dataset Derived from Open Scientific Literature to Advance Biomedical Generalist AI

arXiv:2503.22727v3 Announce Type: replace Abstract: Despite the excitement behind biomedical artificial intelligence (AI), access to high-quality, diverse, and large-scale data - the foundation for mo

researcharxiv-cs-cl

A Learning Algorithm for Threshold Boolean Networks with Prescribed Fixed Points

arXiv:2609.20298v1 Announce Type: new Abstract: We present a learning algorithm for inferring threshold Boolean networks (TBNs) with a prescribed set of fixed points. The proposed method employs a cus

A Mathematical Model of Motivated Emotional Mind - Cognitive Embodied System

arXiv:2609.20437v1 Announce Type: cross Abstract: This article presents a mathematical model of the Motivated Emotional Mind cognitive architecture developed for embodied intelligent systems. Such a s

A Morphing Aerial Robot With Thruster-Integrated Flexible Continuum Links for Shape Adaptive Aerial Manipulation

arXiv:2609.19328v1 Announce Type: new Abstract: In recent years, aerial manipulation has attracted increasing attention as a key to expand the application of aerial robots. In this work, we focus on t

researcharxiv-cs-ro

A Multi-Modal Generative Model for Tomato Disease Leaves Understanding

arXiv:2609.19555v1 Announce Type: cross Abstract: Artificial intelligence for plant disease analysis has advanced from task-specific classifiers to multi-modal models capable of jointly interpreting v

A Multi-Objective Optimisation Framework for Corticomuscular EEG-EMG Pair Selection in Hybrid BCI

arXiv:2609.20275v1 Announce Type: cross Abstract: Hybrid brain-computer interface (BCI) systems that integrate electroencephalography (EEG) and electromyography (EMG) signals have shown significant po

A Network Science Approach to Granular Time Series Segmentation

model-releasesarxiv-cs-lg

arXiv:2505.17640v3 Announce Type: replace Abstract: Time series segmentation assigns a label to each part of a sequence. We formulate dense univariate segmentation as node classification on a graph wh

A Neuropsychologically Grounded Evaluation of LLM Cognitive Abilities

model-releasesarxiv-cs-ai

arXiv:2603.02540v2 Announce Type: replace Abstract: Large language models (LLMs) display a unified 'general factor' of capability across 10 benchmarks (a finding confirmed by our factor analysis of 15

A Noise Optimum in Rehearsal-Free Continual Learning: Isolation, Mechanism, and Scope

arXiv:2609.20162v1 Announce Type: new Abstract: Injecting stochastic noise into a consolidation rule can improve a network's retention of earlier tasks up to an optimal level, then degrade it -- an in

safetyarxiv-cs-lg