Knowledge catalogue
arXiv:2607.04683v1 Announce Type: cross Abstract: Vision-language models (VLMs) perform well on visual question answering with high-quality images but struggle when questions require knowledge beyond
DOGE shut down USAID, established by JFK in 1961. Before being shut down, the US Agency for International Development (USAID) was the largest funding agency for humanitarian and development aid worldw
arXiv:2607.04469v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) commit multiple tokens per denoising step by decoding each selected position independently from the shared conte
arXiv:2607.03093v1 Announce Type: cross Abstract: Thinking has emerged as a critical capability for Large Language Models (LLMs) tackling complex tasks. However, its reactive nature, where reasoning i
arXiv:2607.03027v1 Announce Type: new Abstract: The decline of human balance control due to aging and pathological conditions increases fall risk, a major concern in geriatric care and rehabilitation.
arXiv:2607.04740v1 Announce Type: new Abstract: Spatial Transcriptomics (ST) measures gene expression while preserving spatial context, but its high cost and low throughput leave public datasets small
arXiv:2607.04941v1 Announce Type: new Abstract: Full-duplex spoken dialogue models are trained on conversational speech in which each speaker is represented as a separate stream, but existing large-sc
arXiv:2602.08923v2 Announce Type: replace Abstract: Multi-hop all-reduce is the de facto backbone of large model training. As the training scale increases, the network often becomes a bottleneck, moti
arXiv:2508.12116v2 Announce Type: replace-cross Abstract: As numerous instruction-tuning datasets continue to emerge, dynamically balancing and optimizing their mixtures has become a critical challeng
arXiv:2607.04112v1 Announce Type: cross Abstract: Multimodal LLMs struggle to systematically model the temporal evolution of visual scenes in videos or multi-image sequences. Such inputs require model
arXiv:2607.02866v1 Announce Type: new Abstract: Event-based 3D tracking enables low-latency and high-speed perception, while existing CNN- and Transformer-based trackers struggle to capture long-range
arXiv:2607.03174v1 Announce Type: cross Abstract: Software diversity has been extensively studied as a means of reducing the risk of common-mode failures. Classic work showed that the central issue is
arXiv:2607.04030v1 Announce Type: cross Abstract: Conditional functional dependencies (CFDs) are functional dependencies with a restricted scope: they specify the context in which a dependency holds a
arXiv:2603.00205v2 Announce Type: replace-cross Abstract: Generative models, particularly Diffusion Models (DM), have shown strong potential for Computed Tomography (CT) reconstruction serving as expr
arXiv:2602.17284v2 Announce Type: replace Abstract: We consider the privacy amplification properties of a sampling scheme in which a user's data isused in k steps chosen randomly and uniformly from a
arXiv:2607.03752v1 Announce Type: cross Abstract: Measuring the extent to which emergent languages encode the visual content of their inputs is an open problem. We refer to this property as visual ref
arXiv:2607.02981v1 Announce Type: cross Abstract: Recent advancements in the Internet of Things (IoT) emphasize the urgent need for advanced network security, as IoT networks feature dynamic topologie
arXiv:2607.04069v1 Announce Type: cross Abstract: Cardiac cine Magnetic Resonance Imaging (MRI) is a critical diagnostic tool that provides dynamic insights for radiologists. To accelerate acquisition
arXiv:2607.02562v1 Announce Type: new Abstract: Learned video codecs based on continuous latent representations struggle to operate reliably below 0.1 bits per pixel~(bpp): without a differentiable ra
arXiv:2607.03568v1 Announce Type: cross Abstract: Objective: Accurate identification of acute ischemic infarcts on diffusion-weighted magnetic resonance imaging (DWI) is a critical prerequisite for re
arXiv:2501.11086v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown tremendous promise in automated software engineering. In this paper, we investigate LLMs for just-in-t
arXiv:2607.04814v1 Announce Type: cross Abstract: Extending automatic speech recognition (ASR) to low-resource African languages is constrained by the prohibitive demands of data collection at scale.
arXiv:2607.02623v1 Announce Type: new Abstract: Time series foundation models (TSFMs) have shown strong zero-shot forecasting performance, but their generalization in covariate-driven, non-stationary
arXiv:2512.22240v5 Announce Type: replace-cross Abstract: Machine learning models are primarily judged by predictive performance, especially in applied genomics, where explanations are read as biologi
arXiv:2607.04548v1 Announce Type: cross Abstract: Novel category discovery aims to identify unseen classes from unlabeled data by transferring knowledge from labeled categories, but most existing meth
arXiv:2504.17331v3 Announce Type: replace-cross Abstract: Locomotion plays a crucial role in shaping the user experience within virtual reality environments. In particular, hands-free locomotion offer
arXiv:2511.19636v2 Announce Type: replace-cross Abstract: In many machine learning problems, there may exist multiple models that achieve nearly identical predictive performance while relying on funda
arXiv:2607.04062v1 Announce Type: cross Abstract: We study the fundamental classification problem of computing a separating hyperplane for a binary-labeled dataset of size n with normalized d-dimensio
arXiv:2508.02641v2 Announce Type: replace-cross Abstract: Molecular crystal structure prediction (CSP) is essential for applications in pharmaceuticals and organic electronics. However, CSP remains ch
arXiv:2511.06454v3 Announce Type: replace-cross Abstract: We analyze an algorithm for assigning weights prior to scalarization in discrete multi-objective problems arising from data analysis. The algo
arXiv:2607.04170v1 Announce Type: new Abstract: Federated Learning (FL) enables decentralized training without data sharing, but suffers from statistical heterogeneity across clients, leading to clien
arXiv:2607.03387v1 Announce Type: new Abstract: Tactile perception is indispensable for contact-rich manipulation, yet integrating it into Vision-Language-Action (VLA) models often induces modality co
arXiv:2607.04449v1 Announce Type: new Abstract: Field-boundary maps support crop monitoring, irrigation planning, and yield estimation, but many smallholder parcels span only a few 10 m Sentinel-2 pix
arXiv:2607.04461v1 Announce Type: new Abstract: Inference-time scaling for text-to-image generation has progressed from simple Best-of-N (BoN) sampling to guided search methods that verify and steer c
arXiv:2504.07337v2 Announce Type: replace Abstract: Aggregating temporal signals from historic interactions is a key step in future link prediction on dynamic graphs. However, incorporating long histo
arXiv:2602.05305v3 Announce Type: replace-cross Abstract: Generating long-form content, such as minute-long videos and extended texts, is increasingly important for modern generative models. Block dif
arXiv:2607.03787v1 Announce Type: new Abstract: Accurately modeling biomolecular interactions is a central bottleneck in biology and therapeutic discovery. Here, we introduce Open Drug Discovery Engin
arXiv:2607.03798v1 Announce Type: cross Abstract: Symmetry is everywhere in nature and society. Geometric deep learning exploits symmetries in data to improve the performance and efficiency of deep le
arXiv:2603.19834v3 Announce Type: replace Abstract: Novel view synthesis has recently been revolutionized by 3D Gaussian Splatting (3DGS), which enables real-time rendering through explicit primitive
arXiv:2602.16512v2 Announce Type: replace Abstract: Prompting schemes such as Chain of Thought, Tree of Thoughts, and Graph of Thoughts can significantly enhance the reasoning capabilities of large la
arXiv:2607.03323v1 Announce Type: new Abstract: Masculinity in nineteenth-century fiction is not a single ideal but a field of competing scripts. Drawing on 150 British and American canonical novels f
arXiv:2607.04501v1 Announce Type: cross Abstract: The ability to automatically infer analytic intent from user interaction histories could enable interactive AI systems to proactively assist users dur
arXiv:2607.03394v1 Announce Type: new Abstract: Real time location data derived from mobile applications is a powerful tool for addressing various urban challenges, including tourism planning, parking
arXiv:2607.02574v1 Announce Type: cross Abstract: The key-value (KV) cache has become a first-order memory object in LLM serving rather than a temporary per-request tensor. This survey classifies more
arXiv:2607.03994v1 Announce Type: cross Abstract: Modern language models generally represent text as sequences of discrete token embeddings, an assumption deeply rooted in current practice but rarely
arXiv:2607.02977v1 Announce Type: new Abstract: Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments
arXiv:2607.02612v1 Announce Type: cross Abstract: Vision Transformers achieve strong image classification accuracy but process all image regions with nearly the same computation, even when many region
arXiv:2412.12640v2 Announce Type: replace Abstract: The increasing demand for data privacy, alongside the benefits of aggregating data from networked devices, has catalyzed the emergence of federated
arXiv:2607.05257v1 Announce Type: new Abstract: Origin-destination (OD) flow modeling underpins urban planning and mobility analysis, but prevailing graph-based methods often neglect salient geographi
arXiv:2607.04500v1 Announce Type: new Abstract: Self-supervised latent world models can assign a surprise score to driving scenarios without any human labels. A natural follow-up question is whether s
arXiv:2607.05354v1 Announce Type: new Abstract: Monocular-to-stereo conversion synthesizes stereoscopic content from 2D videos for immersive 3D experiences. In modern Depth-Image-Based Rendering (DIBR
arXiv:2607.04977v1 Announce Type: new Abstract: Accurately estimating the unknown target label distribution is the critical first step for adapting to label shift. This task, widely known as quantific
arXiv:2607.05162v1 Announce Type: new Abstract: Navigational bronchoscopy is critical for pulmonary interventions, yet current platforms depend heavily on pre-operative CT or external sensors, limitin
arXiv:2607.03760v1 Announce Type: new Abstract: The deployment of large-scale foundation models like Segment Anything Model (SAM) on resource-constrained Earth observation platforms is hindered by pro
arXiv:2312.15320v3 Announce Type: replace-cross Abstract: Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests, and genetic
arXiv:2607.04117v1 Announce Type: cross Abstract: ERA5 seasonal climate variables contain predictive information about future glacier retreat beyond what satellite imagery alone provides, yet existing
arXiv:2607.04673v1 Announce Type: new Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer lit
arXiv:2603.06121v2 Announce Type: replace Abstract: Gaze and speech are promising interaction modalities for individuals with motor impairments, yet robust intent recognition in multi-object environme
arXiv:2607.02712v1 Announce Type: new Abstract: Novel View Synthesis (NVS) enables the generation of unseen views of a scene from a single or multiple images, allowing users to freely explore an objec
arXiv:2512.16396v2 Announce Type: replace-cross Abstract: We establish L^p-universal approximation theorems for general path-dependent and non-anticipative functionals on suitable rough path spaces, s