Knowledge catalogue
arXiv:2604.10647v1 Announce Type: new Abstract: UMI-style interfaces enable scalable robot learning, but existing systems remain largely visuomotor, relying primarily on RGB observations and trajector
arXiv:2604.09795v1 Announce Type: cross Abstract: This paper investigates a planar tracking problem between a leader and follower agent. We propose a novel feedback speed control law, paired with a co
arXiv:2512.22142v2 Announce Type: replace-cross Abstract: The foundation-model ecosystem remains highly centralized because training requires immense compute resources and is therefore largely limited
arXiv:2604.10064v1 Announce Type: new Abstract: Multimodal Transformers serve as the backbone for state-of-the-art vision-language models, yet their quadratic attention complexity remains a critical b
arXiv:2604.11480v1 Announce Type: new Abstract: We show that deciding whether an argument a is stronger than an argument b with respect to the discussion-based semantics of Amgoud and Ben-Naim is deci
arXiv:2506.05249v4 Announce Type: replace Abstract: Transformer models have emerged as fundamental tools across various scientific and engineering disciplines, owing to their outstanding performance i
arXiv:2512.15564v2 Announce Type: replace Abstract: Remote sensing (RS) image segmentation is constrained by the limited availability of annotated data and a gap between overhead imagery and natural i
arXiv:2604.11720v1 Announce Type: cross Abstract: The proliferation of autoregressive (AR) image generators demands reliable detection and attribution of their outputs to mitigate misinformation, and
arXiv:2604.11403v1 Announce Type: cross Abstract: Analyzing unsteady fluid flows often requires access to the full distribution of possible temporal states, yet conventional PDE solvers are computatio
arXiv:2604.10672v1 Announce Type: cross Abstract: Density ratio estimation (DRE) is a useful tool for quantifying discrepancies between probability distributions, but existing approaches often involve
arXiv:2604.10814v1 Announce Type: new Abstract: We study online covariance matrix estimation for Polyak--Ruppert averaged stochastic gradient descent (SGD). The online batch-means estimator of Zhu, Ch
arXiv:2502.07114v2 Announce Type: replace-cross Abstract: Given the ubiquity of streaming data, online algorithms have been widely used for parameter estimation, with second-order methods particularly
arXiv:2511.19651v2 Announce Type: replace Abstract: Control barrier functions (CBFs) are an effective model-based tool to formally certify the safety of a system. With the growing complexity of modern
arXiv:2604.11411v1 Announce Type: new Abstract: Reasoning video object segmentation predicts pixel-level masks in videos from natural-language queries that may involve implicit and temporally grounded
arXiv:2604.10087v1 Announce Type: new Abstract: We present EL-DRUIN, an ontological reasoning system for geopolitical intelligence analysis that combines formal ontology, finite semigroup algebra, and
arXiv:2604.11477v1 Announce Type: new Abstract: The alignment of Multi-Agent Systems (MAS) for autonomous software engineering is constrained by evaluator epistemic uncertainty. Current paradigms, suc
arXiv:2604.09580v1 Announce Type: new Abstract: Standard Chain-of-Thought (CoT) prompting empowers Large Language Models (LLMs) with reasoning capabilities, yet its reliance on linear natural language
arXiv:2604.09581v1 Announce Type: new Abstract: Evaluating web usability typically requires time-consuming user studies and expert reviews, which often limits iteration speed during product developmen
arXiv:2602.17314v2 Announce Type: replace-cross Abstract: Open datasets play a crucial role in three research domains that intersect data science and education: learning analytics, educational data mi
arXiv:2604.11587v1 Announce Type: new Abstract: This paper introduces Bidirectional Tight Informed Trees (BTIT*), an asymptotically optimal kinodynamic sampling-based motion planning algorithm that in
arXiv:2601.13844v2 Announce Type: replace Abstract: We study generalization in an overparameterized continual linear regression setting, where a model is trained with L2 (isotropic) regularization acr
arXiv:2510.02779v3 Announce Type: replace Abstract: Recent advances have significantly improved our understanding of the generalization performance of gradient descent (GD) methods in deep neural netw
arXiv:2604.11026v1 Announce Type: cross Abstract: We study the problem of characterizing the stability of Kullback-Leibler (KL) divergence under Gaussian perturbations beyond Gaussian families. Existi
arXiv:2512.07661v3 Announce Type: replace Abstract: Realistic and diverse multi-agent driving scenes are crucial for evaluating autonomous vehicles, but safety-critical events which are essential for
arXiv:2504.06307v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) has led to significant energy consumption and carbon emissions, posing a critical challenge
arXiv:2604.10412v1 Announce Type: cross Abstract: Conditional effects are commonly used measures for understanding how treatment effects vary across different groups, and are often used to target trea
arXiv:2604.09709v1 Announce Type: cross Abstract: Recent bilinear feed-forward replacements for vision transformers can substantially improve accuracy, but they often conflate two effects: stronger se
arXiv:2604.09643v1 Announce Type: new Abstract: Three-dimensional (3D) handheld photoacoustic tomography typically relies on bulky and expensive external positioning sensors to correct motion artifact
arXiv:2604.11523v1 Announce Type: new Abstract: We are entering an era in which individuals and organizations increasingly deploy dedicated AI agents that interact and collaborate with other agents. H
arXiv:2604.02244v3 Announce Type: replace-cross Abstract: This is an extended version of our publication Learning state machines from data streams: A generic strategy and an improved heuristic, Intern
arXiv:2602.23390v2 Announce Type: replace-cross Abstract: Opinion polarization moderation has been studied mainly as an analytical optimization problem under the Friedkin Johnson FJ model, where inter
arXiv:2604.11484v1 Announce Type: new Abstract: On-the-Fly Category Discovery (OCD) requires a model, trained on an offline support set, to recognize known classes while discovering new ones from an o
arXiv:2604.11808v1 Announce Type: new Abstract: Generating high-fidelity 3D indoor scenes remains a significant challenge due to data scarcity and the complexity of modeling intricate spatial relation
arXiv:2604.11061v1 Announce Type: cross Abstract: Mechanistic interpretability is often motivated for alignment auditing, where a model's verbal explanations can be absent, incomplete, or misleading.
arXiv:2604.11004v1 Announce Type: cross Abstract: In this work, we introduce a new perspective on comparative image assessment by representing an image pair as a structured composition of its regions.
arXiv:2601.07447v2 Announce Type: replace Abstract: Existing image foundation models are not optimized for spherical images having been trained primarily on perspective images. PanoSAMic integrates th
arXiv:2604.11307v1 Announce Type: new Abstract: Leveraging Multi-modal Large Language Models (MLLMs) to accelerate frontier scientific research is promising, yet how to rigorously evaluate such system
arXiv:2604.09556v1 Announce Type: cross Abstract: Mixed-integer programming (MIP) extends linear programming by incorporating both continuous and integer decision variables, making it widely used in p
arXiv:2601.15593v2 Announce Type: replace-cross Abstract: Masked Diffusion Language Models (MDLMs) promise parallel token generation and arbitrary-order decoding, yet it remains unclear to what extent
arXiv:2604.10451v1 Announce Type: new Abstract: Despite recent advancements in the field of medical image analysis with the use of pretrained foundation models, the issue of distribution shifts betwee
arXiv:2604.10085v1 Announce Type: new Abstract: We propose a robust alignment technique for Standard Fundus Images (SFIs) and Ultra-Widefield Fundus Images (UWFIs), which are challenging to align due
arXiv:2604.09863v1 Announce Type: cross Abstract: The goal of domain adaptation is to make predictions for unlabeled samples from a target domain with the help of labeled samples from a different but
arXiv:2604.09701v1 Announce Type: new Abstract: Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recy
arXiv:2412.11390v3 Announce Type: replace-cross Abstract: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the brain and external devices. Howeve
arXiv:2604.10481v1 Announce Type: cross Abstract: Retrieving the correct set of files from a large codebase is a crucial step in Automated Program Repair (APR). High recall is necessary to ensure that
arXiv:2512.07222v3 Announce Type: replace-cross Abstract: To address the trade-off between robustness and performance for robust VLM, we observe that function words could incur vulnerability of VLMs a
arXiv:2604.10475v1 Announce Type: new Abstract: Modeling household-level trip generation is fundamental to accurate demand forecasting, traffic flow estimation, and urban system planning. Existing stu
arXiv:2604.10531v1 Announce Type: cross Abstract: Peptide therapeutics are widely regarded as the 'third generation' of drugs, yet progress in peptide Machine Learning (ML) are hindered by the absence
arXiv:2604.10730v1 Announce Type: cross Abstract: The availability and increasing integration of generative AI tools have transformed computing education. While AI in education presents opportunities,
arXiv:2604.10439v1 Announce Type: new Abstract: Purpose: Existing deep learning-based MRI artifact correction models exhibit poor clinical generalization due to inherent artifact-tissue confusion, fai
arXiv:2511.14393v2 Announce Type: replace Abstract: In our work, we extend the current state-of-the-art approach for autonomous multi-UAV exploration to consumer-level UAVs, such as the DJI Mini 3 Pro
arXiv:2604.09829v1 Announce Type: new Abstract: Gaze-following in child-robot interaction improves attention, recall, and learning, but requires expensive platforms ($30,000+), sensors, algorithms, an
arXiv:2506.01201v2 Announce Type: replace Abstract: David Marr's seminal theory of human perception stipulates that visual processing is a multi-stage process, prioritizing the derivation of boundary
arXiv:2604.11645v1 Announce Type: cross Abstract: Frequency-selective wireless power transfer provides a feasible route to enable independent actuation and control of multiple untethered robots in a c
arXiv:2604.09588v1 Announce Type: new Abstract: Modern AI agents suffer from a fundamental identity problem: when context windows overflow and conversation histories are summarized, agents experience
arXiv:2604.11120v1 Announce Type: new Abstract: Personality imbuing customizes LLM behavior, but safety evaluations almost always study prompt-based personas alone. We show this is incomplete: prompti
arXiv:2604.11565v1 Announce Type: new Abstract: We show that short-range phoneme dependencies encode large-scale patterns of linguistic relatedness, with direct implications for quantitative typology
arXiv:2604.10125v1 Announce Type: new Abstract: Existing single-image 3D indoor scene generators often produce results that look visually plausible but fail to obey real-world physics, limiting their
arXiv:2602.14812v3 Announce Type: replace Abstract: Physical commonsense reasoning represents a fundamental capability of human intelligence, enabling individuals to understand their environment, pred
arXiv:2602.13847v3 Announce Type: replace-cross Abstract: We present a framework for constructing physics and causally constrained neural models of turbulent dynamical systems from data. We first form