Knowledge catalogue
arXiv:2608.21806v1 Announce Type: cross Abstract: Computational resources are increasingly central to NLP research, but how closely reported GPU capability aligns with scholarly impact remains unclear
arXiv:2608.23023v1 Announce Type: new Abstract: An LLM router picks which model should answer each query. The appeal is that models fail on different questions. Whatever single model is best overall s
arXiv:2608.22337v1 Announce Type: cross Abstract: Speech-guided referring video object segmentation aims to recover the mask tracks of objects specified by a spoken motion description. Here, speech ca
arXiv:2608.22398v1 Announce Type: cross Abstract: Reliably tracking moving deformable linear objects (DLOs) while simultaneously ensuring robustness, accuracy, and temporally consistent state estimati
arXiv:2608.22045v1 Announce Type: cross Abstract: Modern scientific facilities and instruments generate datasets at scales that are difficult for individual researchers to discover, access, and explor
arXiv:2608.23247v1 Announce Type: cross Abstract: We introduce multi-winner voting with argumentative ballots (MVArg) and investigate theoretical properties. As our conceptual contribution, we general
arXiv:2608.21481v1 Announce Type: cross Abstract: We participated in the BIC-MAC Challenge with a multimodal 3D patch-based U-Net for pseudo-CT generation from NAC-PET, MRI, and 2D topograms. By using
arXiv:2608.21678v1 Announce Type: cross Abstract: Current work in modeling symbolic music primarily relies on representations extracted from MIDI-like data. While such formats allow for modeling symbo
arXiv:2608.22555v1 Announce Type: cross Abstract: The significant upsurge in vehicle traffic presents a considerable challenge in the pursuit of smart mobilization and transportation (SMT) worldwide.
arXiv:2608.22888v1 Announce Type: new Abstract: Reconstructing photorealistic scenes in unconstrained underwater environments remains challenging due to severe media-induced light scattering and unpre
arXiv:2608.21588v1 Announce Type: cross Abstract: Under mild assumptions, any quantum mechanical (QM) model or quantum field theory (QFT) admits a representation in terms of an ensemble of neural netw
arXiv:2608.22782v1 Announce Type: cross Abstract: The Solar wind is a continuous flow of charged particles emanating from the solar surface and governed by complex, interacting magnetohydrodynamic pro
arXiv:2305.19802v2 Announce Type: replace-cross Abstract: Factor analysis (FA) is a statistical method for explaining how mutually dependent observed variables can be represented in terms of mutually
arXiv:2608.21962v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate register-transfer-level (RTL) designs from natural-language specifications. However, as
arXiv:2608.22785v1 Announce Type: new Abstract: Spatial multi-omics technologies jointly profile gene expression, surface proteins, and histology at each tissue spot, yet most spatial domain discovery
arXiv:2608.22302v1 Announce Type: new Abstract: The case when a partial differential equation (PDE) can be considered as an Euler-Lagrange (E-L) equation of an energy functional, consisting of a data
arXiv:2602.23633v2 Announce Type: replace Abstract: Stochastic Bilevel Optimization has emerged as a fundamental framework for meta-learning and hyperparameter optimization. Despite the practical prev
arXiv:2608.21376v1 Announce Type: cross Abstract: Many NLP tasks require systems to provide attribution in their outputs--i.e. citations to grounding sources. Attribution serves as a bulwark against m
arXiv:2608.23476v1 Announce Type: new Abstract: Narrow fine-tuning on small, domain-specific datasets can produce broad and surprising changes in model behavior-a phenomenon called weird generalizatio
arXiv:2608.22972v1 Announce Type: new Abstract: Surgical action triplet recognition constitutes a critical task in context-aware robot-assisted surgery, facilitating automatic surgical action percepti
arXiv:2602.16642v4 Announce Type: replace Abstract: Neural Collapse (NC) refers to the emergence of highly symmetric geometric structures in the representations of deep neural networks during the term
arXiv:2602.24013v2 Announce Type: replace Abstract: Generative image models such as diffusion models can improve performance on clinically relevant tasks by offering deep learning models supplementary
arXiv:2608.21819v1 Announce Type: cross Abstract: Reliable image captioning in Vision-Language Models (VLMs) requires captions to be both precise and complete, avoiding unsupported object mentions whi
arXiv:2608.23410v1 Announce Type: new Abstract: Photorealistic novel view synthesis of people remains challenging at high spatial resolutions and across multiple target cameras, where preserving ident
arXiv:2608.21892v1 Announce Type: cross Abstract: The electronic circular dichroism (ECD) spectrum is a primary experimental probe for assigning the absolute configuration of chiral molecules, yet int
arXiv:2608.23562v1 Announce Type: cross Abstract: Ballistocardiography (BCG) is promising for unobtrusive long-term blood pressure (BP) monitoring in laboratory settings, but traditional BCG signals a
arXiv:2608.21767v1 Announce Type: new Abstract: Accurate modeling of sea ice concentration (SIC) evolution is essential for polar climate assessment and short?range sea ice prediction. Numerical and d
arXiv:2608.21645v1 Announce Type: cross Abstract: Motivated by equivariant neural networks, we study piecewise linear equivariant maps between finite-dimensional real representations of compact groups
arXiv:2608.21885v1 Announce Type: new Abstract: Pixel-space diffusion models directly model image distributions but remain difficult to optimize. Recent methods alleviate this challenge through target
arXiv:2608.23287v1 Announce Type: new Abstract: Count data represented as a matrix of non-negative integer values, such as contingency tables, are prevalent across diverse domains. When clustering suc
arXiv:2608.23101v1 Announce Type: cross Abstract: Recent progress in the field of TinyML has demonstrated that low-power hardware based on microcontrollers can achieve bird species monitoring in real
arXiv:2606.16077v2 Announce Type: replace-cross Abstract: In this paper, we introduce a polynomial-time version of the mistake-bounded language generation (MBLG) framework due to Kleinberg, Peale, and
arXiv:2608.23086v1 Announce Type: new Abstract: Black-box large language models need confidence scores that can separate likely-correct from likely-incorrect outputs, enabling systems to prioritize hu
arXiv:2608.21646v1 Announce Type: cross Abstract: TinyML systems are enabling machine learning (ML) inference at the edge. However, there is little quantitative analysis of such systems. This paper pr
arXiv:2608.23531v1 Announce Type: new Abstract: Older adults recovering after lower-limb fracture or hip replacement may experience complex recovery trajectories. Most of the time, these clinical aspe
arXiv:2608.21543v1 Announce Type: cross Abstract: Object placement is critical in image composition, requiring spatially and semantically coherent positioning of objects within diverse scenes. Existin
arXiv:2608.22097v1 Announce Type: cross Abstract: Pathologic complete response (pCR) is a strong neoadjuvant endpoint, yet 5-15% of complete responders recur and clinical/genomic variables do not reli
arXiv:2608.23480v1 Announce Type: cross Abstract: Timely risk classification is essential in many clinical monitoring settings, where decisions must balance the benefit of classifying patients early f
arXiv:2608.22388v1 Announce Type: cross Abstract: Propaganda detection includes several related prediction levels, ranging from sentence-level decisions to technique classification and span identifica
arXiv:2601.22754v2 Announce Type: replace-cross Abstract: Industrial troubleshooting guides encode diagnostic procedures in flowchart-like diagrams where spatial layout and technical language jointly
arXiv:2608.23554v1 Announce Type: new Abstract: Discrete diffusion models offer a promising alternative to autoregressive generation by enabling parallel updates, but their sampling efficiency can dep
arXiv:2608.22887v1 Announce Type: new Abstract: Large language models (LLMs) are entering decisions in triage and lending, where task-relevant inference must be distinguished from impermissible proxy
arXiv:2608.21874v1 Announce Type: cross Abstract: Deep learning has achieved strong performance in encrypted traffic classification (ETC), yet its computational cost limits deployment on resource-cons
arXiv:2608.22475v1 Announce Type: new Abstract: We study parameterized quantum circuits (PQCs) integrated as residual sidecar modules within a ResNet-50 backbone for 31-class neural population decodin
arXiv:2608.21597v1 Announce Type: cross Abstract: Clinical data sources such as electronic health records and wearable sensors record patient status repeatedly over follow-up, often at irregular times
arXiv:2608.21591v1 Announce Type: new Abstract: Multi-horizon rare-event forecasting is hard under long macroeconomic series' data constraints: labeled events are scarce, and standard uncertainty quan
arXiv:2608.21582v1 Announce Type: new Abstract: World models built on the RSSM architecture, such as DreamerV3, keep a recurrent hidden state h_t trained only to reduce prediction error. We show this
arXiv:2608.22786v1 Announce Type: new Abstract: Multimodal graph learning requires jointly training over graph structure and heterogeneous node attributes, yet existing methods largely decouple these
arXiv:2608.21881v1 Announce Type: new Abstract: We describe our approach to the Big Cross-Modal Attenuation Correction (BIC-MAC) challenge, which asks for a pseudo-CT in Hounsfield Units to be synthes
arXiv:2606.14892v2 Announce Type: replace Abstract: An artificial intelligence must have a model of its environment that is causal, supporting reasoning about interventions and counterfactuals, and al
arXiv:2608.21482v1 Announce Type: cross Abstract: Background: Multimodal fracture classifiers may benefit from patient and anatomical metadata, but they can also become brittle when contextual informa
arXiv:2608.22914v1 Announce Type: new Abstract: This report summarizes the contributions and results of the 1st Asynchronous CASTLE Challenge at the Joint Egocentric Vision Workshop in conjunction wit
arXiv:2608.23241v1 Announce Type: cross Abstract: Identifying and classifying environmental mitigation obligations in Federal Energy Regulatory Commission hydropower licensing documents is a labor-int
arXiv:2608.22054v1 Announce Type: new Abstract: Structure-from-Motion (SfM) aims to estimate camera poses and reconstruct 3D structures from a collection of unordered images. Compared with incremental
arXiv:2608.21583v1 Announce Type: new Abstract: Oral cancer is a leading cause of mortality in low-to-middle-income countries, where a shortage of specialists delays diagnosis. While point-of-care scr
arXiv:2608.23419v1 Announce Type: cross Abstract: Information Retrieval (IR) systems seek to identify relevant documents within a collection. In practical applications, collections are dynamic, with d
arXiv:2510.01262v2 Announce Type: replace-cross Abstract: Accurate prediction of train delays is critical for efficient railway operations. While earlier approaches have largely focused on forecasting
arXiv:2608.22979v1 Announce Type: new Abstract: Deploying high-dimensional multimodal features in industrial recommender systems incurs substantial storage and latency overhead. Hard quantization is c
arXiv:2608.22354v1 Announce Type: cross Abstract: Delta-Rule recurrent models maintain a fixed-size state, enabling O(1) inference memory but potentially becoming unstable under extreme-context extrap
arXiv:2503.05916v2 Announce Type: replace-cross Abstract: Accurate segmentation of anatomical structures in ultrasound (US) images, particularly small ones, is challenging due to noise and variability