Knowledge catalogue
arXiv:2609.22228v1 Announce Type: new Abstract: Large language models increasingly rely on long chain-of-thought (CoT) trajectories for complex reasoning, but autoregressive generation brings substant
arXiv:2609.22141v1 Announce Type: cross Abstract: Automated seizure detection from scalp electroencephalography (EEG) is difficult because seizure morphology varies among patients and seizure samples
arXiv:2609.23053v1 Announce Type: new Abstract: A RAG system can hand you the right answer and cite a source it did not actually use. Models output these unfaithful citations via post-rationalization:
arXiv:2609.24218v1 Announce Type: new Abstract: Audio-based localization provides a low-cost and illumination-independent sensing solution for anti-UAV early warning. However, existing methods typical
arXiv:2609.23979v1 Announce Type: cross Abstract: Attention encoder-decoder (AED) Speech Foundation Models achieve strong ASR performance but can generate acoustically unsupported text when inputs con
arXiv:2609.24059v1 Announce Type: new Abstract: Semantically meaningful subtask labels can provide useful contexts for long-horizon policies, but automatically identifying both reliable temporal bound
arXiv:2609.22635v1 Announce Type: cross Abstract: Three-dimensional fetal brain ultrasound offers non-ionizing, cost-effective imaging with rich spatial information for comprehensive anatomical assess
arXiv:2609.23646v1 Announce Type: cross Abstract: E-commerce search requires distinguishing products that are merely related to a query from those that directly satisfy the user's shopping intent. We
arXiv:2609.22095v1 Announce Type: cross Abstract: Electrodermal activity (EDA) is widely used in automatic stress detection, yet most pipelines treat it only as a raw one-dimensional waveform. This st
arXiv:2609.22149v1 Announce Type: new Abstract: Multimodal synthetic datasets combine structured attributes with free text, but are often evaluated separately. Such metrics can remain high after tabul
arXiv:2609.22291v1 Announce Type: new Abstract: This paper presents a comprehensive experimental evaluation and detailed analysis of state-of-the-art multi-object tracking algorithms, with an emphasis
arXiv:2609.24612v1 Announce Type: new Abstract: Model merging aims to consolidate multiple task-specific models without access to extra training process. However, existing subspace-based methods large
arXiv:2510.06145v2 Announce Type: replace Abstract: We tackle the problem of forecasting bimanual 3D hand motion and articulation from a single image in everyday settings. To address the lack of 3D ha
arXiv:2609.23717v1 Announce Type: new Abstract: Global vision--language similarities compress an image and a caption into one vector, preserving semantics but not which word corresponds to which regio
arXiv:2609.23352v1 Announce Type: new Abstract: Bimanual interaction produces complementary tactile views of the same physical process, yet existing tactile representation learning largely models the
arXiv:2609.23268v1 Announce Type: new Abstract: Blind image deconvolution (BID) is a prominent research topic in the field of imaging sciences, given its significant practical applications. Most exist
arXiv:2609.24769v1 Announce Type: new Abstract: Brain metastases are the most common intracranial malignancy, occurring in roughly 30% of patients with primary solid tumors and carrying a median survi
arXiv:2609.22282v1 Announce Type: new Abstract: Reconstructing visual stimuli from electroencephalography (EEG) is difficult because scalp measurements have high temporal but limited spatial resolutio
arXiv:2609.24088v1 Announce Type: new Abstract: In latent generative models, reconstruction quality is often assumed to correlate with generative performance. However, reconstruction FID (rFID) can ex
arXiv:2609.24052v1 Announce Type: new Abstract: Crash datasets that carry an investigator narrative hold information the coded fields omit. Coding those narratives at scale has been blocked by three o
arXiv:2609.22252v1 Announce Type: new Abstract: We present CALM, a reproducible hybrid framework that integrates an optional large language model (LLM) activity planner with calibrated stochastic choi
arXiv:2609.24841v1 Announce Type: new Abstract: Multi-robot systems have shown increasing viability in construction due to their ability to execute high-precision actions while reducing human exposure
arXiv:2609.23219v1 Announce Type: new Abstract: Unobserved confounding is a fundamental challenge in causal inference from observational data. This article develops a mixture-learning perspective, vie
arXiv:2609.22274v1 Announce Type: new Abstract: Recent advances in humanoid robotics have produced diverse skills through reinforcement learning, motion imitation, and generative modeling. Yet these c
arXiv:2512.04723v2 Announce Type: cross Abstract: Human Action Recognition using WiFi Channel State Information (CSI) has emerged as an attractive alternative to vision-based methods due to its ubiqui
arXiv:2609.22632v1 Announce Type: new Abstract: We study binary classification with abstention under separate class-conditional error constraints, with the objective of minimizing abstention while kee
arXiv:2609.22950v1 Announce Type: new Abstract: While compressed-sensing regularizers enable interpretable reconstruction of 4D Flow CMR through transparent variational objectives, their hand-crafted
arXiv:2609.24394v1 Announce Type: new Abstract: Climate variability influences whether a market disruption escalates into a food crisis, yet broad climate patterns like El Nino, tracked months before
arXiv:2609.22734v1 Announce Type: new Abstract: Clinical domain classification plays an important role in organizing and analyzing large volumes of unstructured medical text. However, medical transcri
arXiv:2508.03749v2 Announce Type: replace Abstract: Accurately estimating urban rail platform occupancy can support more informed operational decision-making by transit agencies, particularly during p
arXiv:2609.22232v1 Announce Type: new Abstract: Millions worldwide require Renal Replacement Therapy (RRT) as a treatment essential for survival. However, optimizing RRT strategies via AI is challengi
arXiv:2609.23883v1 Announce Type: new Abstract: We present a collaborative streaming anomaly detection system for high-speed data streams that explicitly integrates human analysts into the decision lo
arXiv:2609.23961v1 Announce Type: new Abstract: Monocular colonoscopic 3D reconstruction is important for surgical robotic colonoscopy, but remains challenging due to weak texture, specular reflection
arXiv:2301.12254v5 Announce Type: replace-cross Abstract: Assortment optimization has received active explorations in the past few decades due to its practical importance. Despite the extensive litera
arXiv:2609.23619v1 Announce Type: new Abstract: Snapshot hyperspectral imaging avoids sequential scanning, but systems that jointly achieve stable reconstruction, low cost, and compact optics remain l
arXiv:2609.22105v1 Announce Type: cross Abstract: Automatic sleep staging from polysomnography (PSG) is a well-studied task, but PSG itself is expensive, clinic-based, and burdensome to manually score
arXiv:2609.23476v1 Announce Type: cross Abstract: A potential path forward is Quantum Machine Learning (QML), which aims to leverage quantum computing in conjunction with classical machine learning to
arXiv:2609.22284v1 Announce Type: new Abstract: Talking-face (TF) deepfakes are detected unevenly by rPPG-based methods across generators. We study two lightweight visual-only cues, rPPG-derived wavef
arXiv:2609.22415v1 Announce Type: new Abstract: Complex-valued Transformers have inherited softmax attention over the raw complex inner product. Outside natively complex domains this standard form sta
arXiv:2609.24423v1 Announce Type: cross Abstract: We consider a standard convex composite optimization problem with either smooth or nonsmooth objective function, and under quadratic growth. In recent
arXiv:2609.23005v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables high-quality novel view synthesis but incurs high storage and transmission costs due to dense Gaussian primitives.
arXiv:2609.22614v1 Announce Type: new Abstract: Process model forecasting (PMF) aims to predict the process model that will characterize a future period, thereby providing a process-level view of how
arXiv:2609.23815v1 Announce Type: new Abstract: Medical image segmentation models typically rely on large amounts of densely annotated volumetric data, limiting their scalability across tasks and imag
arXiv:2609.24929v1 Announce Type: cross Abstract: In this paper, we study nonasymptotic L^p error bounds for interval length and conditional coverage in split conformalized quantile regression (CQR).
arXiv:2609.22983v1 Announce Type: cross Abstract: Robotic grasping is typically formulated as the problem of identifying successful actions from a space of candidate grasp poses. However, the organiza
arXiv:2609.22101v1 Announce Type: new Abstract: Large language models can process increasingly long prompts, yet their ability to locate and use decisive evidence may degrade as irrelevant or confusab
arXiv:2609.22487v1 Announce Type: new Abstract: Matrix-valued optimizer states may contain relational structure that is not captured by treating their entries independently. We study whether relations
arXiv:2609.22553v1 Announce Type: new Abstract: Effective LLM tutoring depends on correctly identifying the specific error in a student's reasoning before generating feedback. We study this problem in
arXiv:2609.22131v1 Announce Type: new Abstract: Structured pruning is a promising approach for reducing the substantial inference costs of Large Language Models (LLMs) while maintaining hardware effic
arXiv:2609.22187v1 Announce Type: cross Abstract: Spatial transcriptomics (ST) provides spatially resolved gene expression profiling but remains expensive, motivating the prediction of ST from histolo
arXiv:2609.23094v1 Announce Type: cross Abstract: We study the number of prototypes needed to represent Boolean functions by nearest-neighbour classification. There are two distinct settings: the prot
arXiv:2609.24382v1 Announce Type: new Abstract: The intensification of climate change poses a growing threat to food security, especially in vulnerable communities. This study employs an observational
arXiv:2609.23320v1 Announce Type: new Abstract: Social bot detection is essential for protecting online platforms from misinformation amplification, coordinated manipulation, and distorted public disc
arXiv:2609.22760v1 Announce Type: cross Abstract: Purpose: A vertebra at the lumbosacral junction is named by counting caudally from C2 on whole-spine imaging, but a lumbar case is planned on lumbar-o
arXiv:2609.22494v1 Announce Type: new Abstract: In recent years, there has been a surge of interest in Cultural NLP, with substantial efforts to create globally inclusive NLP systems. The rapid growth
arXiv:2609.22862v1 Announce Type: new Abstract: Graph neural networks are widely used for drug--target affinity (DTA) prediction, and discrete Ricci curvature has recently been used to characterize mo
arXiv:2609.24625v1 Announce Type: cross Abstract: How should natural language processing models be selected and adapted for global health literature in environments where annotated data and computatio
arXiv:2609.22276v1 Announce Type: new Abstract: The Dynamic Window Approach (DWA) is widely used for local navigation, but its performance depends strongly on parameters that are typically fixed befor
arXiv:2609.22941v1 Announce Type: new Abstract: Novel view synthesis from sparse inputs remains challenging for 3D Gaussian Splatting (3DGS) due to ambiguous geometry, cross-view inconsistency, and mi
arXiv:2609.24409v1 Announce Type: new Abstract: Multi-task visual grounding requires models to jointly understand linguistic semantics and perform accurate visual localization and segmentation. Despit