Knowledge catalogue
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
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
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
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
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
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
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.
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
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
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
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
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:
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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-
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
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
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
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
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
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
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
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
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
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
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
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
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
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
arXiv:2609.19736v1 Announce Type: new Abstract: This paper proposes a phonemically comprehensive, ASCII-only romanization scheme for Thai and Lao, treating the two closely related languages as a unifi
arXiv:2609.19640v1 Announce Type: new Abstract: Croissant is the de facto machine-readable descriptor for ML datasets: JSON-LD over schema.org. Since version 1.1 it also carries data use conditions, r
arXiv:2609.20080v1 Announce Type: new Abstract: The growing complexity of multi-domain operational environments (land, aerospace, naval, cyber, and electromagnetic spectrum) has increased the volume a
arXiv:2609.20349v1 Announce Type: new Abstract: Spatial reasoning abilities correlate strongly with performance in STEM fields. Games offer a compelling medium for training these critical skills in de
arXiv:2609.20095v1 Announce Type: cross Abstract: The Internet of Agents is expected to enable large numbers of autonomous agents to discover, verify, and collaborate with each other across heterogene
arXiv:2609.20620v1 Announce Type: cross Abstract: Autonomous underwater vehicles (AUVs) operating beyond reliable communications must recover from failures without human intervention. We investigate a
arXiv:2609.20100v1 Announce Type: new Abstract: Recent findings indicate that Vision Transformers settle into locally similar computational phases, implying a level of depthwise computational redundan
arXiv:2609.20276v1 Announce Type: cross Abstract: Many applications must repeatedly evaluate an expensive function f of a sorted score vector whose influence decays with rank: Plackett-Luce choice pro
arXiv:2609.20222v1 Announce Type: new Abstract: Cataract is a major cause of vision loss and hinders further diagnosis. However, cataract fundus image enhancement often grapples with challenges such a
arXiv:2609.19524v1 Announce Type: new Abstract: Benchmark scores alone provide an incomplete basis for assessing the trustworthiness of modern artificial intelligence systems. Large language models (L
arXiv:2609.19812v1 Announce Type: new Abstract: Traditional scene understanding focuses on affirmative information objectively present in images. However, in safety-critical domains, comprehending key
arXiv:2609.20359v1 Announce Type: cross Abstract: The symbiotic scaling of artificial intelligence models and high-performance computing systems continually creates algorithmic challenges in their con