Knowledge catalogue
arXiv:2608.16180v1 Announce Type: new Abstract: To combat oversmoothing in Graph Convolutional Networks, Sheaf Neural Networks (SNNs) were proposed as a generalization by equipping the graph with a sh
arXiv:2608.15851v1 Announce Type: cross Abstract: LLM-based query expansion improves retrieval by generating document-like passages. In hybrid retrieval, however, most evaluations fuse fixed top-L den
arXiv:2608.16506v1 Announce Type: cross Abstract: Dataset alignment is a central step in data analysis across science and engineering, where the goal is to match observations between datasets. Entropi
arXiv:2608.15881v1 Announce Type: new Abstract: The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source finite-element framework for building multiphysics simulation applicat
arXiv:2608.16367v1 Announce Type: new Abstract: To date, all natural scene skeleton detection follows the paradigm of taking RGB images as the sole input; despite notable progress, methods under this
arXiv:2608.16014v1 Announce Type: new Abstract: Achieving reliable single-shot high dynamic range (HDR) imaging under extreme illumination conditions remains a long-standing challenge, yet no comprehe
arXiv:2603.23924v2 Announce Type: replace Abstract: Text-to-image models often struggle to synthesize correct occlusion relationships among multiple objects, especially in densely overlapping regions.
arXiv:2608.16728v1 Announce Type: new Abstract: Designing large soft robots capable of generating high forces for physical human-robot interaction remains a significant challenge in soft robotics. Pri
arXiv:2608.15461v1 Announce Type: new Abstract: Reconfigurable robots offer significant potential for adapting to diverse tasks; however, conventional centralized architectures often require dedicated
arXiv:2608.15447v1 Announce Type: new Abstract: Mobile money has widened financial access across Sub-Saharan Africa and enlarged the surface for money-laundering and terrorism-financing (ML/TF) activi
arXiv:2601.04798v2 Announce Type: replace Abstract: Robust long-term tracking of drone is a critical requirement for modern surveillance systems, given their increasing threat potential. While detecto
arXiv:2608.14935v1 Announce Type: cross Abstract: Turbulent fluxes between the surface and the atmosphere are typically parameterized using empirically fit relationships. Here we test machine learning
arXiv:2608.14655v1 Announce Type: cross Abstract: Omni-Large Language Models (Omni-LLMs) power complex multi-modal reasoning in applications like World Action Models and autonomous agents. However, th
arXiv:2608.16805v1 Announce Type: cross Abstract: Large vision-language models can recognize the objects and attributes in a crowded scene yet assign an attribute to the wrong same-class instance. Gen
arXiv:2505.14107v5 Announce Type: replace-cross Abstract: The emergence of groundbreaking large language models capable of performing complex reasoning tasks holds significant promise for addressing v
arXiv:2603.11249v4 Announce Type: replace Abstract: Accurate prediction of phase equilibria remains a central challenge in chemical engineering. Physics-consistent machine learning methods that incorp
arXiv:2603.27151v2 Announce Type: replace-cross Abstract: Radiance field reconstruction aims to recover high-quality 3D representations from multi-view RGB images. Recent advances, such as 3D Gaussian
arXiv:2504.00944v2 Announce Type: replace-cross Abstract: We propose a numerical method of searching for parameters with experimental constraints in generic flavor models by utilizing diffusion models
arXiv:2608.16159v1 Announce Type: cross Abstract: Digital Twins (DTs) are increasingly used to monitor and analyze Cyber Physical Systems (CPS). However, in adversarial environments, the fidelity of a
arXiv:2405.07780v3 Announce Type: replace-cross Abstract: This paper explores test-agnostic long-tail recognition, a challenging long-tail task where the test label distributions are unknown and arbit
arXiv:2510.00358v2 Announce Type: replace-cross Abstract: Soft snake robots offer remarkable flexibility and adaptability in complex environments, yet their control remains challenging due to highly n
arXiv:2608.14851v1 Announce Type: new Abstract: Learning and skill mastery require extensive and deliberate practice. In many learning settings, producing high-quality pedagogical materials can requir
arXiv:2608.14649v1 Announce Type: new Abstract: We present dLLM-SetScore, a training-free method that uses discrete masked-diffusion language models for multi-label text classification. For each candi
arXiv:2608.14823v1 Announce Type: new Abstract: Are heterophilic nodes in a graph harder to classify because they are heterophilic or because they are rare? Some existing work frames classification of
arXiv:2607.01503v2 Announce Type: replace Abstract: In this paper, we study depth perception of vision-language models (VLMs) to isolate the effects of pictorial depth cues and disentangle vision and
arXiv:2608.14916v1 Announce Type: cross Abstract: AI-generated music detectors are commonly evaluated against original songs, but real-world uploads are often remixed, re-encoded, pitch-shifted, or ot
arXiv:2608.15090v1 Announce Type: new Abstract: Studies of industrial visual inspection commonly report the area under the receiver operating characteristic curve (AUROC) and the overlap between anoma
arXiv:2608.15303v1 Announce Type: new Abstract: Test-time compute can substantially improve Large Language Model (LLM) reasoning performance, yet how and when additional compute helps remains poorly u
arXiv:2608.15630v1 Announce Type: cross Abstract: The rapid development and growing deployment of large language models (LLMs) have made it increasingly important to understand their capabilities. A c
arXiv:2608.14729v1 Announce Type: new Abstract: Fake/synthetic images are increasingly prevalent, but it remains unclear whether Convolutional Neural Networks (CNNs) process real and fake images in th
arXiv:2608.14982v1 Announce Type: cross Abstract: Transformers applied to spatial imperfect-information games must represent map geometry while tracking hidden entities through time. We ask whether ge
arXiv:2608.15507v1 Announce Type: new Abstract: A consistent concept of the current time is important for temporal reasoning, yet how language models represent the current time is not well understood.
arXiv:2608.14613v1 Announce Type: new Abstract: Modern LLM-agent frameworks increasingly interoperate through standards such as Anthropic's Model Context Protocol (MCP) for agent-to-tool access and Go
arXiv:2608.14808v1 Announce Type: new Abstract: When a user question is underspecified, a capable model should recognize that its context is insufficient, identify the missing information, ask for it,
arXiv:2608.14653v1 Announce Type: cross Abstract: Prediction uncertainty is a widely adopted metric for quantifying model confidence, with downstream applications spanning model explanation, data sele
arXiv:2608.15061v1 Announce Type: new Abstract: Do feed-forward networks (FFNs) in visual grounding decoders add essential computation once a pretrained vision-language model has already encoded image
arXiv:2608.15365v1 Announce Type: new Abstract: Regret minimization (RM) and best-arm identification (BAI) are two fundamental objectives in multi-armed bandits. Among regret-minimizing algorithms, 1/
arXiv:2608.14992v1 Announce Type: new Abstract: Language-model systems increasingly read from stores they also write to, so a claim that was merely written earlier can return looking retrieved. We tes
arXiv:2607.14882v2 Announce Type: replace-cross Abstract: With a large controlled vocabulary as the label set, the task of automated subject indexing in a library can be understood as a multi-label cl
arXiv:2608.14662v1 Announce Type: cross Abstract: Accurate recognition of pain using physiological signals remains a challenging problem due to pain's subjective nature and high inter-individual varia
arXiv:2608.16671v1 Announce Type: new Abstract: The language-model head maps a hidden state of width D to a vocabulary of size V, so its transpose can return at most D independent directions to the Tr
arXiv:2608.15432v1 Announce Type: new Abstract: In formal verification, both the autoformalization of statements and automated proof search have been studied extensively. While automated proof search
arXiv:2608.16269v1 Announce Type: new Abstract: Recent advances in neural topic models with pre-trained language models (PLMs) have achieved strong performance by leveraging general-domain pre-trainin
arXiv:2608.14693v1 Announce Type: cross Abstract: With the increasing digitization of personal and corporate communication, the automatic sanitization of textual data has become a crucial component of
arXiv:2608.16161v1 Announce Type: cross Abstract: General-purpose text embedding models are designed to capture semantic similarity but are not optimised for distinguishing entity records that represe
arXiv:2608.16889v1 Announce Type: cross Abstract: Long-horizon robot manipulation chains many contact-rich skills into one multi-stage task. Vision-language-action (VLA) models increasingly master the
arXiv:2211.14297v4 Announce Type: replace-cross Abstract: We introduce and analyze an improved variant of nearest neighbors (NN) for estimation with missing data in latent factor models. We consider a
arXiv:2608.16640v1 Announce Type: new Abstract: Vision-based Unmanned Aerial Vehicles (UAVs) often suffer from navigation failures in dead ends due to limited sensing accuracy and range. To address th
arXiv:2608.16632v1 Announce Type: new Abstract: Deep learning-based object detectors are fundamental to intelligent transportation systems, enabling traffic monitoring, vehicle analytics, and infrastr
arXiv:2502.11603v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particul
arXiv:2608.16435v1 Announce Type: new Abstract: In collection operations, accumulating payload progressively slows the vehicle, imposing a cumulative penalty on routing efficiency. An onboard drone ca
arXiv:2608.16354v1 Announce Type: new Abstract: Driving video generation models support autonomous-driving development by predicting controllable future scenes for simulation, planning evaluation, and
arXiv:2412.19505v3 Announce Type: replace Abstract: Recent successes in autoregressive (AR) generation models, such as the GPT series in natural language processing, have motivated efforts to replicat
arXiv:2511.20270v2 Announce Type: replace Abstract: Anomaly detection in industrial visual inspection is challenging due to the scarcity of defective samples. Most existing methods rely on unsupervise
arXiv:2608.16536v1 Announce Type: cross Abstract: Multimodal Retrieval Augmented Generation (M-RAG) is increasingly vulnerable to adversarial attacks where malicious data are crafted to produce embedd
arXiv:2608.15423v1 Announce Type: cross Abstract: Sea surface temperature (SST) is a critical indicator of global climate change, yet satellite-derived SST imagery often suffers from coarse spatial re
arXiv:2608.15019v1 Announce Type: cross Abstract: Breast mass segmentation is an important step in computer-aided mammography, but it remains difficult because masses can have low contrast, irregular
arXiv:2608.14644v1 Announce Type: cross Abstract: Real-world LLM deployments increasingly rely on runtime-injected prohibitions--enterprise policies, PII redlines, tool boundaries--that vary per reque
arXiv:2608.14614v1 Announce Type: cross Abstract: As AI datacenters retire functional GPUs, vast quantities of still capable accelerators enter secondary markets. This paper investigates whether these
arXiv:2608.16053v1 Announce Type: new Abstract: Synthetic conversational speech has become an important resource for developing and evaluating conversational speech systems. However, existing dialogue