Knowledge catalogue
arXiv:2604.18491v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is central to race-car aerodynamic development, yet its cost -- tens of thousands of core-hours per high-fidelity eva
arXiv:2604.17110v1 Announce Type: new Abstract: Clinical AI development has traditionally followed a collaborative paradigm that depends on close interaction between clinicians and specialized AI team
arXiv:2602.16213v2 Announce Type: replace-cross Abstract: This paper introduces a novel approach to sea ice modeling using Graph Neural Networks (GNNs), utilizing the natural graph structure of sea ic
arXiv:2604.16422v1 Announce Type: new Abstract: The injection of domain-specific knowledge is crucial for adapting language models (LMs) to specialized fields such as biomedicine. While most current a
arXiv:2604.16381v1 Announce Type: new Abstract: This report provides a summary of the outcomes of the Interdisciplinary Workshop on Mechanical Intelligence held in 2024. Mechanical Intelligence (MI) r
arXiv:2604.16915v1 Announce Type: new Abstract: Retrieval augmented generation (RAG) has transformed text based question answering, yet its extension to visual domains remains hindered by fundamental
arXiv:2512.20626v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) enables large language models (LLMs) to dynamically access external information, which is powerful for an
arXiv:2604.17390v1 Announce Type: new Abstract: Ancient inscriptions frequently suffer missing or corrupted regions from fragmentation, erosion, or other damage, hindering reading, and analysis. We re
arXiv:2604.18152v1 Announce Type: cross Abstract: Deep learning (DL) has become a cornerstone of modern machine learning (ML) praxis. We introduce the R package mlr3torch, which is an extensible DL fr
arXiv:2604.16518v1 Announce Type: new Abstract: Satellite constellations are transforming space systems from isolated spacecraft into networked, software-defined platforms capable of on-orbit percepti
arXiv:2601.22002v3 Announce Type: replace Abstract: Transformers achieve superior performance on many tasks, but impose heavy compute and memory requirements during inference. This inference can be ma
arXiv:2506.01770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In
arXiv:2601.18231v4 Announce Type: replace Abstract: Adapting pre-trained models to unseen feature modalities has become increasingly important due to the growing need for cross-disciplinary knowledge
arXiv:2604.16557v1 Announce Type: cross Abstract: Current post-training methodologies for adapting Large Vision-Language Models (LVLMs) generally fall into two paradigms: Supervised Fine-Tuning (SFT)
arXiv:2604.18177v1 Announce Type: new Abstract: Benchmarks are often used as a standard to understand LLM capabilities in different domains. However, aggregate benchmark scores provide limited insight
arXiv:2604.16585v1 Announce Type: new Abstract: We present the Global Neural World Model (GNWM), a self-stabilizing framework that achieves topological quantization through balanced continuous entropy
arXiv:2604.16536v1 Announce Type: new Abstract: Machine learning components are now central to AI-infused software systems, from recommendations and code assistants to clinical decision support. As re
arXiv:2604.18208v1 Announce Type: new Abstract: Symmetric objects are common in daily life and industry, yet their inherent orientation ambiguities that impede the training of deep learning networks f
arXiv:2510.05336v2 Announce Type: replace Abstract: Historical archives on weather events are collections of enduring primary source records that offer rich, untapped narratives of how societies have
🔴 We're going live tomorrow for another Come Build with Pinecone session! Join us to build, break, and learn together. Each session, we pick up a real project — building RAG pipelines, wiring up agent
arXiv:2601.04609v2 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly used to make visual content accessible via text-based descriptions. In current systems, however, desc
arXiv:2603.14975v2 Announce Type: replace-cross Abstract: Large Language Model agents deployed in complex environments frequently encounter a conflict between maximizing goal achievement and adhering
Wasabi Technologies Inc. today said it has secured a $250 million credit facility, choosing to forego equity financing for the flexibility of debt. The decision highlights an issue that often faces gr
arXiv:2604.15489v1 Announce Type: cross Abstract: The Internet of Medical Things (IoMT) enables intelligent healthcare services but faces challenges such as dynamic topology, energy constraints, and d
Beyond generating high-fidelity visuals, we wanted to test the limits of what Nano Banana Pro can do. We worked with design partners Porto Rocha to build out a hypothetical brand called YOYOYO to see
arXiv:2604.16061v1 Announce Type: cross Abstract: We study discrete k-clustering problems in general metric spaces that are constrained by a combination of two different fairness conditions within the
arXiv:2603.16427v2 Announce Type: replace Abstract: This paper considers self-supervised cross-modal coordination as a strategy enabling utilization of multiple modalities and large volumes of unlabel
arXiv:2604.15593v1 Announce Type: cross Abstract: Large language models compress heterogeneous knowledge into a single parameter space, allowing facts from different domains to interfere during genera
arXiv:2604.15865v1 Announce Type: new Abstract: Series and parallel elastic actuators offer complementary but mutually exclusive advantages, yet no existing actuator enables real-time transition betwe
Emad Mostaque announced the release of Stability AI's first paper, microsite, and integration with NotebookLM, likely detailing new research findings or technical capabilities. The announcement appear
arXiv:2504.01137v3 Announce Type: replace Abstract: Text-to-image generation models suffer from alignment problems, where generated images fail to accurately capture the objects and relations in the t
arXiv:2604.15482v1 Announce Type: cross Abstract: Large Language Models (LLMs) unlearning is crucial for removing hazardous or privacy-leaking information from the model. Practical LLM unlearning dema
arXiv:2510.23536v2 Announce Type: replace Abstract: Intent identification serves as the foundation for generating appropriate responses in personalized question answering (PQA). However, existing benc
arXiv:2604.15760v1 Announce Type: new Abstract: We introduce the first version of KWBench (Knowledge Work Bench), a benchmark for unprompted problem recognition in large language models: can an LLM id
arXiv:2604.16054v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have achieved impressive progress on vision language benchmarks, yet their capacity for visual cognitive and
Cloudflare discusses their approach to implementing AI-powered code review systems across large-scale development operations, likely covering how they leverage AI models to automate code quality check
Yann LeCun was right the entire time. And generative AI might be a dead end. For the last three years, the entire industry has been obsessed with building bigger LLMs. Trillions of parameters. Billion
arXiv:2604.15376v1 Announce Type: cross Abstract: Multi-step zoom-in pipelines are widely used for GUI grounding, yet the intermediate predictions they produce are typically discarded after coordinate
This post discusses the mathematical principle that when attempting a 1/n probability event n times, the probability of at least one success converges to approximately 63.2% (mathematically 1 - 1/e ≈
Agentic Engineering Patterns > Here's an example of a deceptively short prompt that got a lot of work done in a single shot. First, some background. I send out a free Substack newsletter around once a
arXiv:2604.14779v1 Announce Type: cross Abstract: In continual visual question answering (VQA), existing Continual Learning (CL) methods are mostly built for symmetric, unimodal architectures. However
arXiv:2602.08698v2 Announce Type: replace Abstract: This study examines the practical applications and methodological implications of Machine Translation in Indian Languages, specifically Bangla, Mala
arXiv:2604.14747v1 Announce Type: new Abstract: Solving non-linear least-squares problem for pose estimation (rotation and translation) is often a time consuming yet fundamental problem in several rea
arXiv:2604.14188v1 Announce Type: cross Abstract: Large language models have demonstrated impressive performance across many domains of mathematics and physics. One natural question is whether such mo
Grok 4.3 Beta is insanely good and now comes with powerful new tools that are super helpful for everyday use: • Create clean slides, graphs, images and dashboards • Pull real-time data and images dire
arXiv:2604.14507v1 Announce Type: new Abstract: As a classic vision task, anomaly detection has been widely applied in industrial inspection and medical imaging. In this task, data scarcity is often a
arXiv:2510.02539v2 Announce Type: replace Abstract: Neural document retrieval often treats a corpus as a flat cloud of vectors scored at a single granularity, leaving corpus structure underused and ex
arXiv:2604.14632v1 Announce Type: new Abstract: Conventional RGB-based high dynamic range (HDR) imaging faces a fundamental trade-off between motion artifacts in multi-exposure captures and irreversib
arXiv:2602.10069v2 Announce Type: replace Abstract: Human factors research has long focused on optimizing environments, tools, and systems to account for human performance. Yet, as humanoid robots beg
arXiv:2408.14728v2 Announce Type: replace Abstract: Adversarial training has proven effective in improving the robustness of deep neural networks against adversarial attacks. However, this enhanced ro
arXiv:2502.04689v4 Announce Type: replace Abstract: Intent, a critical cognitive notion and mental state, is ubiquitous in human communication and problem-solving. Accurately understanding the underly
arXiv:2604.15107v1 Announce Type: cross Abstract: Feature selection is a classical problem in statistics and machine learning, and it continues to remain an extremely challenging problem especially in
arXiv:2604.14198v1 Announce Type: cross Abstract: Domain reweighting can improve sample efficiency and downstream generalization, but data-mixture optimization for multimodal midtraining remains large
arXiv:2604.14216v1 Announce Type: cross Abstract: Predicting post-surgical seizure outcomes in pharmacoresistant epilepsy is a clinical challenge. Conventional deep-learning approaches operate on stat
arXiv:2506.13139v2 Announce Type: replace-cross Abstract: Modern Machine Learning (ML) and Deep Neural Networks (DNNs) often operate on high-dimensional data and rely on overparameterized models, wher
This post likely advocates for treating longer time periods with the same urgency and attention to detail as shorter ones, suggesting a productivity or time management approach where months receive th
This is a pixel art illustration by David Ha depicting a scene of waiting for departure, likely showing characters or a scene at a transportation hub or travel location rendered in pixel art style. Th
arXiv:2604.15280v1 Announce Type: new Abstract: Understanding emotions is a fundamental ability for intelligent systems to be able to interact with humans. Vision-language models (VLMs) have made trem
arXiv:2604.13059v1 Announce Type: new Abstract: Most dialogue-based electronic medical record (EMR) systems still behave as passive pipelines: transcribe speech, extract information, and generate the
arXiv:2604.13369v1 Announce Type: cross Abstract: Surrogate modeling of body-driven fluid flows where immersed moving boundaries couple structural dynamics to chaotic, unsteady fluid phenomena remains