Knowledge catalogue
arXiv:2607.28624v1 Announce Type: new Abstract: We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing phys
arXiv:2603.11325v2 Announce Type: replace Abstract: Low-field to high-field MRI synthesis has emerged as a promising strategy to improve image quality when access to high-field scanners is limited. Ho
arXiv:2602.04635v2 Announce Type: replace Abstract: Robots are finding wider adoption in human environments, increasing the need for natural human-robot interaction. However, understanding a natural l
arXiv:2607.27271v1 Announce Type: new Abstract: Code models are increasingly trained with execution feedback, but most training signals still stop at correctness. This leaves an important gap for syst
arXiv:2607.27835v1 Announce Type: new Abstract: Accurate cell segmentation and classification are foundational to digital pathology, enabling quantitative tissue analysis for diagnosis and treatment p
arXiv:2607.28525v1 Announce Type: new Abstract: Many real-world graphs support multiple predictive tasks over the same underlying structure, creating an opportunity to reuse supervision across node cl
arXiv:2601.13732v2 Announce Type: replace Abstract: The fact that robots are getting deployed more often in dynamic environments, together with the increasing complexity of their software systems, rai
arXiv:2607.28261v1 Announce Type: new Abstract: Video re-shooting aims to regenerate videos with controllable camera motion and viewpoint. Existing methods rely on explicit 3D priors, which are limite
arXiv:2607.27179v1 Announce Type: cross Abstract: Conversational AI is increasingly positioned as a teammate rather than a tool, yet we know little about how its presence reshapes communication among
arXiv:2408.06083v2 Announce Type: replace Abstract: In the field of monocular depth estimation (MDE), many models with excellent zero-shot performance in general scenes emerge recently. However, these
arXiv:2607.27966v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) have recently emerged as a promising paradigm for general-purpose graph learning, aiming to learn reusable knowledge that
arXiv:2511.07210v3 Announce Type: replace Abstract: Clean-image backdoor attacks, which use only label manipulation in training datasets to compromise deep neural networks, pose a significant threat t
arXiv:2607.26752v1 Announce Type: new Abstract: Medical world models aim to learn a latent state of patient or organ physiology and a transition function that forecasts how that state evolves under in
arXiv:2505.06945v5 Announce Type: replace Abstract: Multimodal data modeling has emerged as a powerful approach in clinical research, enabling the integration of diverse data types such as imaging, ge
arXiv:2607.26458v1 Announce Type: cross Abstract: Domain generalization (DG) aims to learn from multiple source domains and generalize to unseen target domains. Most DG methods pursue invariance: they
arXiv:2607.26513v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models rely mainly on 2D inputs, neglecting the rich object structural information and commonsense knowledge inhere
arXiv:2607.26903v1 Announce Type: cross Abstract: The key bottleneck in embodied AI is not model architecture but data. Although billions of human manipulation videos exist online, robots cannot direc
Hi! I'm trying to train my first LoRA, but I'm not sure how to handle the dataset captions. Should I describe everything in the photo, or just specific details? Also, can I train it using different im
Learn how to build an inference meta-monitoring system for Amazon SageMaker AI endpoints using Amazon Quick. This governance layer sits above production ML inference pipelines to continuously track pr
arXiv:2607.26818v1 Announce Type: new Abstract: Audio-video generative models achieve impressive quality but suffer from high latency, making them unsuitable for real-time applications. Although sever
arXiv:2607.26417v1 Announce Type: new Abstract: Sparse-reward reinforcement learning often fails because rollouts from the unassisted evaluation start rarely reach later task stages. Reset curricula a
Learn how I modernized an old codebase of mine using stacked sessions and pull requests in the GitHub Copilot app. The post Stacked sessions and pull requests in the GitHub Copilot app appeared first
arXiv:2607.26754v1 Announce Type: new Abstract: Recent game world models can generate visually realistic and interactive environments conditioned on player actions. However, games are not defined by p
arXiv:2607.26940v1 Announce Type: new Abstract: Ensembles are a standard way to improve the performance and robustness of deep neural networks, but their effectiveness crucially depends on both the qu
arXiv:2607.25516v1 Announce Type: new Abstract: Vision-language-action (VLA) models predict sequential actions to execute tasks specified by language instructions, conditioned on visual observations a
arXiv:2607.24792v1 Announce Type: cross Abstract: Energy utilities still run engineering work management, engineering procurement, and inventory processes on long-lived enterprise asset management pla
arXiv:2607.25200v1 Announce Type: new Abstract: Despite the empirical advantages of deep networks over shallow ones, theoretical depth separations largely concern approximation power, while algorithmi
arXiv:2607.25117v1 Announce Type: cross Abstract: Deep learning models for ECG image classification may achieve high accuracy by exploiting non-physiological visual cues instead of ECG waveform morpho
arXiv:2607.25502v1 Announce Type: new Abstract: Recent training-time defenses against neural backdoors isolate a benign subset from poisoned training data, to learn a backdoor-free model from it. In t
arXiv:2607.25324v1 Announce Type: cross Abstract: Glaucoma is a group of eye diseases that damage the optic nerve, often caused by elevated intraocular pressure. It is a leading cause of irreversible
arXiv:2607.25432v1 Announce Type: new Abstract: Scribble annotations offer an efficient alternative to costly pixel-wise labeling for medical image segmentation, yet in real clinical scenarios, scribb
arXiv:2607.25609v1 Announce Type: cross Abstract: Understanding disease trajectories from longitudinal clinical data remains challenging due to complex temporal dynamics and heterogeneous patient coho
arXiv:2607.25129v1 Announce Type: new Abstract: Medical coding is the task of assigning a set of diagnosis and procedure codes for a hospitalization using recorded notes. It requires aggregating infor
arXiv:2507.00411v2 Announce Type: replace Abstract: Learning from ambiguous labels is a long-standing problem in practical machine learning applications. The purpose of partial label learning (PLL) is
arXiv:2607.25802v1 Announce Type: new Abstract: Most video editing systems still lack explicit layered video representations, limiting their ability to perform realistic compositing, object reuse, and
arXiv:2607.24757v1 Announce Type: cross Abstract: This paper reports on the rapid development and classroom deployment of a Thonny log visualizer built using AI-assisted ``vibe coding'' to make studen
arXiv:2607.25377v1 Announce Type: new Abstract: Medical image visualization requires volumetric rendering algorithms that preserve anatomical fidelity while maintaining high rendering speeds. To addre
arXiv:2607.24861v1 Announce Type: cross Abstract: Question answering (QA) over complex documents requires models to retrieve and integrate evidence distributed across distant document regions and moda
Jensen Huang was asked about the people technology left behind. He didn't offer a plan. He said the gap already closed. Huang: 'All of a sudden artificial intelligence closed that technology divide.'
arXiv:2607.25282v1 Announce Type: cross Abstract: We investigate a normalizing-flow approach for reconstructing parton distribution functions (PDFs) from synthetic matrix-element data. Our framework c
arXiv:2510.12201v2 Announce Type: replace Abstract: As AI becomes more common in everyday living, there is an increasing demand for intelligent systems that are both performant and understandable. Exp
arXiv:2607.24755v1 Announce Type: cross Abstract: This full research paper examines how different forms of learner-AI interaction relate to learning outcomes in object-oriented programming (OOP) cours
arXiv:2607.25590v1 Announce Type: new Abstract: How to monetize large language models (LLMs) by naturally integrating sponsored content into their responses, known as LLM-native advertising, has recen
arXiv:2607.24991v1 Announce Type: cross Abstract: Context: Generative AI (GenAI) and Large Language Models (LLMs) are increasingly used for academic tasks in software engineering and beyond, including
arXiv:2607.26040v1 Announce Type: new Abstract: Much like humans benefit from guidance while learning, reinforcement learning algorithms may benefit from additional supervision beyond rewards. Leverag
NVIDIA tutorial: StarCoder2-7B NIM behind NeMo Guardrails, plus CI checks and commit trailers so generated patches stay auditable.
arXiv:2607.25337v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn world models by predicting in representation space rather than reconstructing pixels, making them
arXiv:2607.25014v1 Announce Type: new Abstract: In practical settings, medical image segmentation models are often developed with limited annotated data rather than fully labeled datasets. Training fr
arXiv:2607.25636v1 Announce Type: new Abstract: Convolutional neural networks (CNN) for near-infrared (NIR) chemometrics are often designed using generic architectural rules, although spectral dataset
arXiv:2607.25236v1 Announce Type: new Abstract: Different research lines use the term world model in different ways, yet they share a common aim: to capture how the world evolves under action in a for
arXiv:2607.23733v1 Announce Type: cross Abstract: Firms struggle to choose AI projects that pay off: two projects can look equally promising to smart, motivated stakeholders and yet deserve opposite d
At the core of our mission is working through how to ensure increasingly powerful AI benefits everyone. We believe that, at some point in the future, AI acceleration for frontier model development may
arXiv:2607.24110v1 Announce Type: new Abstract: Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception. While cros
arXiv:2607.22919v1 Announce Type: cross Abstract: Multimodal embedding spaces in models like CLIP enable powerful capabilities such as semantic similarity retrieval and cross-modal zero-shot classific
arXiv:2607.23209v1 Announce Type: new Abstract: Infrared unmanned aerial vehicle (UAV) tracking is challenging because the target is often small, low-contrast, and easily confused with thermal distrac
arXiv:2607.22728v1 Announce Type: new Abstract: Automated grading of Lumbar Disc Degeneration is essential for the objective quantification of structural changes associated with low back pain. Observi
arXiv:2607.22880v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have driven growing interest in using LLMs to automate test generation. Prior work commonly evaluates
arXiv:2607.24210v1 Announce Type: new Abstract: In clinical oncology studies, metastatic cancer is commonly evaluated using 'Response Evaluation Criteria in Solid Tumors' (RECIST), in which the diamet
arXiv:2607.23636v1 Announce Type: cross Abstract: Data profiling aims to extract complex patterns from data for further analysis and use that data in domains such as data cleaning, data deduplication,
arXiv:2607.24532v1 Announce Type: new Abstract: Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by ad