Knowledge catalogue
arXiv:2609.17310v1 Announce Type: new Abstract: This study investigates the zero-shot ability of large language models (LLMs) to identify and classify hidden narratives in social messages. Our researc
I implemented expert lookahead, a trick that gets a 10%+ performance improvement on MoE models running on low-memory macs (Qwen 3.8 flash in this case) while using expert-offloading/ssd-streaming (usi
arXiv:2609.14159v1 Announce Type: new Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose early diagnosis remains challenging because conventional clinical assessments are
arXiv:2609.15241v1 Announce Type: new Abstract: Dynamic-vision-sensor (DVS) cameras generate events on a per-pixel basis with a mus-level temporal resolution, calling for new algorithm-hardware co-des
arXiv:2609.14578v1 Announce Type: new Abstract: Autonomous agents that author building information models need more than access to a host API. They need a representation of what they intended, what a
arXiv:2609.15980v1 Announce Type: cross Abstract: When a video model generates physically incorrect motion, did it fail to learn the correct motion, or did it learn it but fail to use it? We show the
arXiv:2609.13255v1 Announce Type: new Abstract: Facial state analysis plays a crucial role in understanding human expressions, psychological modeling, and human computer interaction. Traditional unimo
arXiv:2609.15427v1 Announce Type: cross Abstract: Using food package images to monitor sodium and salt content against South Africa's R214 sodium limits is challenging when screening decisions require
arXiv:2404.00727v3 Announce Type: replace Abstract: All state-of-the-art coreference resolution (CR) models involve finetuning a pretrained language model. Whether the superior performance of one CR m
arXiv:2609.14967v1 Announce Type: new Abstract: Quranic text is distributed in two orthographic forms that are byte-level distinct: the Uthmani script used in every printed mushaf, and the Standard (I
arXiv:2609.13168v1 Announce Type: cross Abstract: Speech AI, any AI system that recognizes, transforms, or generates speech, is built and evaluated across two communities with only a small overlap: te
SemiAnalysis: A deep dive into on-device and data center inference for robots, including a primer on robot models, deployments, supply chains, the “network wall”, and more — Robot Models, Silicon & DR
arXiv:2609.13171v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) use automatic differentiation to impose differential-equation residuals, but good agreement in function values
arXiv:2609.13526v1 Announce Type: cross Abstract: We develop a spectral three-term modification of the classic Hestenes--Stiefel conjugate gradient algorithm, preserving its anti-jamming characteristi
arXiv:2608.25241v2 Announce Type: replace-cross Abstract: Coding agents increase development velocity but also technical debt. Prior work reports only average effects across adopters, hiding wide diff
arXiv:2609.14815v1 Announce Type: cross Abstract: This paper introduces a novel framework for Regularized Multivariate Functional Principal Component Analysis (ReMFPCA) via Functional Singular Value D
arXiv:2609.15389v1 Announce Type: cross Abstract: As artificial intelligence systems increasingly rely on distributed and collaborative training, the energy footprint of these processes becomes a shar
arXiv:2609.14419v1 Announce Type: cross Abstract: Person re-identification (ReID) is essential for multi-camera surveillance and tracking, yet remains difficult due to viewpoint and illumination chang
arXiv:2609.13561v1 Announce Type: new Abstract: Efficient utilization of supply chain analytics for decision making remains a significant challenge for planners, as critical tasks such as database que
arXiv:2609.14413v1 Announce Type: cross Abstract: Large language model (LLM)-based database migration is often treated as direct code transformation, although enterprise Oracle systems contain heterog
arXiv:2609.13481v1 Announce Type: new Abstract: Large language models have made abstractive summarization remarkably fluent, but generated summaries can hallucinate facts, posing serious risks in biom
arXiv:2609.15740v1 Announce Type: cross Abstract: Brain signal analysis is essential for both neuroscience research and clinical diagnostics, yet current approaches face critical limitations. End-to-e
arXiv:2609.14438v1 Announce Type: cross Abstract: When the same question is asked of multiple AI advisers, as in self-consistency and LLM-as-a-judge panels, Condorcet's jury theorem predicts that addi
arXiv:2609.13170v1 Announce Type: cross Abstract: Blockchain-enabled Federated Learning (FL) marketplaces enable collaborative model training among mutually distrustful participants through smart cont
arXiv:2609.13453v1 Announce Type: new Abstract: Earth Observation (EO) data are increasingly organized as spatio-temporal data cubes, while machine learning (ML) methods operate on tabular feature mat
arXiv:2609.14180v1 Announce Type: new Abstract: Fault detection in autonomous VTOL aircraft is critical because even minor component degradations can rapidly destabilize multirotor vehicles operating
arXiv:2609.13878v1 Announce Type: new Abstract: Spatio-temporal traffic data are central to intelligent transportation systems, yet their heterogeneity poses significant challenges for large-scale mod
arXiv:2609.14178v1 Announce Type: new Abstract: The rapid diffusion of hate speech and misinformation on social networks challenges democratic societies, since direct suppression efforts may deepen po
arXiv:2609.14145v1 Announce Type: cross Abstract: Kinship verification is a task involving determining whether two individuals share a first-order kin relation. To tackle this task, we propose CONVTRA
arXiv:2609.14605v1 Announce Type: new Abstract: The agent-centric general value function (ACGVF) construction of itet{tasse2026goal} lets the agent make two decisions that are normally imposed by the
arXiv:2609.14710v1 Announce Type: new Abstract: Interaction paradigms used in robot-assisted autism intervention have historically employed robots as teachers, clinical assistants, or more-abled peers
arXiv:2512.20257v2 Announce Type: replace Abstract: With the rise of easily accessible generative tools for creating and manipulating multimedia content, the threat of realistic synthetic alterations
arXiv:2609.14765v1 Announce Type: cross Abstract: Hip exoskeletons may improve recovery from unexpected gait perturbations, yet personalizing assistance remains difficult because balance is multidimen
arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and
arXiv:2609.14741v1 Announce Type: cross Abstract: Early thermal-mechanical lattice requirements are knowledge-intensive and often jointly unsatisfiable: an engineer asks for a cell that is light, stif
arXiv:2609.13569v1 Announce Type: cross Abstract: Objectives in scientific machine learning are often prescribed as a sum of several terms, such as the residual, boundary, initial, and data losses of
arXiv:2609.14843v1 Announce Type: cross Abstract: AI companions provide socially engaging interaction through availability, personalization, memory, roleplay, and emotionally responsive language. For
arXiv:2603.11667v3 Announce Type: replace Abstract: This paper examines how value is constructed and negotiated in today's increasingly automated language and translation industry. Drawing on intervie
arXiv:2609.13511v1 Announce Type: cross Abstract: Large language models are increasingly benchmarked against classical machine learning for network intrusion detection (NIDS), almost always using same
arXiv:2609.06324v2 Announce Type: replace Abstract: Diffusion language models (dLLMs) predict all tokens of a block in parallel, but a single forward pass samples each position from its own marginal d
arXiv:2609.15603v1 Announce Type: cross Abstract: Accurate PSMA PET/CT interpretation is central to prostate cancer management, yet existing PET/CT AI models typically address isolated tasks. We propo
arXiv:2609.13729v1 Announce Type: new Abstract: We present the Variational Incompressible Optimal Transport (VIOT) operator, a generative neural operator for amortized incompressible density transport
arXiv:2609.15232v1 Announce Type: new Abstract: The introduction of human-robot collaboration (HRC) in industrial assembly operations is revolutionizing the manufacturing landscape. In this evolving e
arXiv:2609.14103v1 Announce Type: cross Abstract: Radiomic texture features are commonly extracted from anisotropic CT and MRI acquisitions, where identical voxel offsets may represent different physi
arXiv:2602.07084v2 Announce Type: replace-cross Abstract: Antigen-antibody binding is a critical process in the immune response. Although recent progress has advanced antibody design, current methods
arXiv:2609.15007v1 Announce Type: new Abstract: Large language models are increasingly used as natural-language interfaces to structured data, yet they remain unreliable when answers require consisten
arXiv:2609.13239v1 Announce Type: new Abstract: Diffusion models represent one of the most advanced paradigms in generative modeling. Leveraging their development, a growing number of style transfer m
arXiv:2609.14105v1 Announce Type: new Abstract: Heat Kernel Textures (HKTex) represent surface appearance with intrinsic anisotropic kernels, but evaluate them using 50 global Laplace-Beltrami eigende
arXiv:2609.15807v1 Announce Type: cross Abstract: As the complexity of High Performance Computing (HPC) ecosys- tems continually increases, achieving optimal performance becomes a challenge. Tradition
arXiv:2609.13840v1 Announce Type: new Abstract: A contract-logistics spare-parts operator is paid on order-level service: an order counts only if every requested line is fulfilled, yet forecasters are
arXiv:2510.23224v2 Announce Type: replace Abstract: The rapid digitization of histopathology slides has opened new opportunities for computational tools in clinical and research workflows. Content-bas
arXiv:2609.14744v1 Announce Type: new Abstract: By acquiring compute, credentials, accounts, services, and other agents, autonomous AI agents can introduce new authority into a task. Payment, budget,
arXiv:2609.14987v1 Announce Type: cross Abstract: Large language model (LLM) agents interact with external environments through tool invocation, but tool outputs can also expose them to indirect promp
arXiv:2502.00550v2 Announce Type: replace Abstract: Surrogate models of parametric dynamical systems are essential for many-query and real-time predictions in engineering applications such as design o
arXiv:2607.19223v2 Announce Type: replace-cross Abstract: Speculative decoding, in which a lightweight draft model first generates a draft sequence that is then verified by the target model, has becom
arXiv:2609.14080v1 Announce Type: new Abstract: Promptable models such as microSAM segment electron microscopy (EM) images from point prompts, but automation requires generating prompts without user i
arXiv:2607.18063v2 Announce Type: replace-cross Abstract: LLM-based agents process external content, exposing them to prompt injection and multi-turn manipulation. We present a 21-scenario benchmark f
arXiv:2609.13303v1 Announce Type: cross Abstract: Medical image classification is frequently complicated by transitional categories whose feature distributions overlap those of adjacent classes, produ
arXiv:2609.13512v1 Announce Type: cross Abstract: Federated fine-tuning of large language models with low-rank adaptation reduces per-client trainable parameters, but client-to-server communication re
arXiv:2609.15131v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) require substantial computation to process numerous visual tokens across all transformer layers. Most methods