Knowledge catalogue
arXiv:2607.03551v1 Announce Type: new Abstract: Weight space learning aims to learn representations of neural network (NN) weights, enabling different downstream tasks. Existing approaches show promis
arXiv:2511.08860v2 Announce Type: replace-cross Abstract: The deep learning revolution has spurred a rise in advances of using AI in sciences. Within physical sciences the main focus has been on disco
arXiv:2607.02885v1 Announce Type: cross Abstract: Cognitive Behavioral Therapy (CBT) provides a structured framework for understanding a user's mental state by examining the interaction between cognit
arXiv:2607.03951v1 Announce Type: cross Abstract: The reproducibility crisis in scientific research has received widespread recognition, thereby increasing the importance of meta-analyses that integra
Ethan Mollick discusses the configuration scope differences between OpenAI and Claude AI systems, distinguishing between global settings that apply across all uses, local machine-specific settings, an
In this post, we walk through how to get started with MiniMax models on Amazon Bedrock, including the capabilities supported by these models, the service tiers available, how on-demand inference scale
Open Knowledge Format (OKF) is a specification from Google Cloud Platform for structuring and managing knowledge data, as referenced in a GitHub repository. Harrison Chase, creator of LangChain, share
This post discusses the evolution of multimodal prompting in AI agent interactions, highlighting how users can now communicate with AI systems using multiple input types beyond text. The author provid
The July 4th weekend All-In @theallinpod turned into a long argument about who owns the intelligence layer. The besties think enterprises just woke up to a trap they had been walking into, here's how
We've created a comprehensive Retrieval Harness for modern agentic retrieval in 2026. The harness provides a persistent data pipeline that can connect to a data source, index and update a large knowle
arXiv:2512.13836v2 Announce Type: replace-cross Abstract: Autonomous driving requires reliable collision avoidance in dynamic environments. Nonlinear Model Predictive Controllers (NMPCs) are suitable
arXiv:2607.01958v1 Announce Type: new Abstract: A/B testing is the gold standard for selecting the better algorithm in online services. While offline evaluation has attracted attention as a safer alte
arXiv:2607.01647v1 Announce Type: cross Abstract: Data science aims to derive actionable insights from heterogeneous raw data, unlocking the value of the massive amounts of data generated in modern so
This dispatch from Latent Space discusses debates within the AI engineering community regarding 'loops' in AI systems and the current state of AI engineering practices. The article likely covers techn
arXiv:2607.02269v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated immense promise in Spatio-Temporal Video Grounding (STVG). However, current evaluation protocols are l
arXiv:2607.01942v1 Announce Type: new Abstract: LLM-based agents have shown strong potential for solving complex multi-step tasks, yet existing performance improvements often rely on either scaling to
arXiv:2607.01679v1 Announce Type: cross Abstract: Adversarial attacks on cybersecurity classifiers pose a dual threat: degrading predictions and destabilising the SHAP-based explanations that security
arXiv:2607.01303v1 Announce Type: cross Abstract: Presentation Attack Detection (PAD) serves as a crucial safeguard for face recognition systems against presentation attacks such as printed photos, re
arXiv:2603.18315v2 Announce Type: replace-cross Abstract: Traditional reinforcement learning (RL) methods rely on manually engineered rewards or sparse collision signals, which fail to capture the ric
arXiv:2607.02166v1 Announce Type: cross Abstract: The rapid advancements in using neural networks as implicit data representations have attracted significant interest in developing machine learning me
arXiv:2606.12569v2 Announce Type: replace-cross Abstract: We present eCream-MedCorpus, a new and unique large-scale dataset of clinical notes produced in Emergency Departments of Italian hospitals. Th
arXiv:2607.02230v1 Announce Type: cross Abstract: The complexity of waste disposal regulations across European countries poses significant challenges for the residents and hinders the transition to a
arXiv:2607.01276v1 Announce Type: cross Abstract: Embedding models are essential components of modern Information Retrieval (IR) systems, yet they are typically hidden behind APIs. Recent works have s
arXiv:2607.02118v1 Announce Type: new Abstract: Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Lar
arXiv:2607.01275v1 Announce Type: cross Abstract: Variational Autoencoders (VAEs) commonly assume a standard isotropic Gaussian prior over the latent space, an assumption that often fails to capture t
Exactly. I've been disseminating a similar message for years. The concentration of power in AI and the desire for control is by far the biggest danger of AI. It could lead to a few private companies a
arXiv:2512.10485v2 Announce Type: replace-cross Abstract: Vulnerability detection methods based on deep learning (DL) have shown strong performance on benchmark datasets, yet their real-world effectiv
This video from Two Minute Papers discusses groundbreaking research by NVIDIA that achieves a 100x speedup in physics-based character animations using AI-powered super-resolution applied to physics si
arXiv:2607.01305v1 Announce Type: cross Abstract: Intrusion Detection Systems (IDSs) are essential for monitoring network traffic and identifying malicious activities in modern cyber-physical, Interne
arXiv:2512.07541v3 Announce Type: replace-cross Abstract: Inspired by graph-based methodologies, we introduce a novel graph-spanning algorithm designed to identify changes in both offline and online d
arXiv:2607.02338v1 Announce Type: cross Abstract: Hierarchical Navigable Small World (HNSW) graphs serve as the industry standard due to their logarithmic complexity and strong empirical performance.
arXiv:2607.01252v1 Announce Type: cross Abstract: Background: Dermatology AI has mainly focused on image-based diagnosis, while chronic disease workflows have received less attention. We surveyed Indi
arXiv:2607.01943v1 Announce Type: new Abstract: Quantum machine learning has recently emerged as a promising paradigm that leverages the expressive power of quantum circuits to address complex learnin
arXiv:2311.17633v2 Announce Type: replace-cross Abstract: Transformers have dominated empirical machine learning models of natural language processing. In this paper, we introduce basic concepts of Tr
arXiv:2607.02472v1 Announce Type: new Abstract: This paper presents a methodology for learning a control policy to intercept an intruder using the 3D direction unit vector to the intruder and the inte
arXiv:2512.02657v2 Announce Type: replace-cross Abstract: Real-world deployment of text-to-image diffusion models requires continual concept removal as new privacy, copyright, or safety obligations ar
arXiv:2607.01539v1 Announce Type: cross Abstract: This paper studies whether the Metabolic Multi-Agent Optimizer (MMAO) can act as a credible outer-loop optimizer for classification model selection. W
arXiv:2607.01814v1 Announce Type: new Abstract: Traditional Chinese Medicine (TCM) diagnosis, particularly through tongue inspection, faces persistent challenges in subjectivity and reproducibility. T
arXiv:2603.27631v2 Announce Type: replace Abstract: Self-supervised pre-training, where large corpora of unlabeled data are used to learn representations for downstream fine-tuning, has become a corne
arXiv:2607.02444v1 Announce Type: cross Abstract: We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown n-qu
arXiv:2607.02512v1 Announce Type: cross Abstract: Many everyday programming tasks resist clean rule-based implementation, such as alerting on important log lines, repairing malformed JSON, or ranking
arXiv:2510.04484v2 Announce Type: replace-cross Abstract: The ability to control LLMs' emulated emotional states and personality traits is an essential step in enabling rich, human-centered interactio
arXiv:2607.02426v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative model training across distributed devices without sharing raw data, making it suitable for privacy-sensi
arXiv:2607.02436v1 Announce Type: cross Abstract: Agentic coding assistants are increasingly given extra capabilities, such as browser based testing tools and design oriented system prompts, on the as
arXiv:2607.01522v1 Announce Type: cross Abstract: Mode shape recognition is a fundamental task in automotive NVH development, yet it remains dependent on manual visual inspection by experienced engine
arXiv:2607.02203v1 Announce Type: new Abstract: Operator learning has emerged as a powerful tool for modeling complex physical systems in functional spaces. However, their neural network-based archite
arXiv:2511.01390v2 Announce Type: replace-cross Abstract: Fine-grained cross-modal alignment aims to establish precise local correspondences between vision and language, forming a cornerstone for visu
arXiv:2604.03497v2 Announce Type: replace-cross Abstract: Vision-language-model (VLM)-guided reinforcement learning (RL) has recently attracted significant attention for it, replacing brittle hand-cra
arXiv:2607.01609v1 Announce Type: new Abstract: Recent advances in Artificial Intelligence (AI) have revolutionized Electronic Design Automation (EDA), particularly through Large Language Models (LLMs
arXiv:2607.01945v1 Announce Type: cross Abstract: The classical k-means clustering cannot be directly used to incomplete data, and existing k-means-based clustering for missing data primarily focus on
arXiv:2607.02494v1 Announce Type: cross Abstract: Models trained via Contrastive Language-Image Pretraining (CLIP) serve as the foundational vision encoders for most modern Large Vision Language Model
arXiv:2607.02447v1 Announce Type: new Abstract: Recent research has introduced distributed self-supervised learning (D-SSL) approaches to leverage vast amounts of unlabeled decentralized data. However
We are pleased to present our latest research at #ICML2026, “Bridging Spherical Black-Box Optimizers” https://arxiv.org/abs/2606.25761 When optimizing through simulators, external APIs, or in reinforc
arXiv:2607.02369v1 Announce Type: cross Abstract: LLMs stage a new form of cultural encounter that is massive, automated, and monolingual. Literary disciplines have always negotiated cultural struggle
Together AI highlights the rapid growth of AI token consumption across multiple companies and teams, noting an increase from 30 billion tokens monthly to 400 trillion annually, with platforms like Cur
arXiv:2607.01145v1 Announce Type: new Abstract: Data analysis in the medical domain often encounters scenarios involving a limited target dataset and a large, unannotated dataset with a general distri
arXiv:2607.00502v1 Announce Type: new Abstract: While long-horizon mobile GUI agents typically rely on thought-action-observation loops, they struggle to separate persistent task states from transient
arXiv:2607.00773v1 Announce Type: new Abstract: Discrete diffusion models are widely used for learning and generating discrete distributions. As the generation process is inherently sequential, the ac
arXiv:2607.01029v1 Announce Type: new Abstract: Collaborative capture of dynamic targets is common in nature as an essential strategy for weaker species against the strong. Similar concepts have shown
The problem of domain generalization concerns learning predictive models that are robust to distribution shifts when deployed in new, previously unseen environments. Existing methods typically require