Knowledge catalogue
The new Cofounder site is literally a step-by-step guide on how to start a company. When i started my first company there was all sorts of stuff i had to learn and all of the guides were SEO maxxed sl
arXiv:2605.10019v1 Announce Type: cross Abstract: Generative models trained on finite data face a fundamental tension: their score-matching or next-token objective converges to the empirical training
arXiv:2605.10373v1 Announce Type: cross Abstract: Large language models have significantly improved natural language interfaces to databases by translating user questions into executable queries. In p
arXiv:2605.10640v1 Announce Type: cross Abstract: Continual Pre-Training (CPT) is essential for enabling Language Models (LMs) to integrate new knowledge without erasing old. While classical CPT techn
arXiv:2605.10567v1 Announce Type: new Abstract: In this paper, we aim to jointly model the geometry, appearance, and physical information of 3D scenes solely from dynamic multi-view videos, without re
arXiv:2605.09908v1 Announce Type: cross Abstract: Current approaches to detecting depression and anxiety from speech primarily rely on machine learning techniques that utilize hand-engineered paraling
arXiv:2605.09461v1 Announce Type: new Abstract: Automated vulnerability detection is a fundamental task in software security, yet existing learning-based methods still struggle to capture the structur
OpenAI confirmed to Ethan Mollick that Study Mode remains active and can be accessed through the /study and /learn shortcuts, though this feature may not be widely known among general users. The acces
arXiv:2605.08298v1 Announce Type: cross Abstract: Reusing the early layers of cohort-trained INRs as initialization for new signals has been shown to accelerate and improve signal fitting, yet it rema
arXiv:2411.18111v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) that incorporate visual models and large language models have achieved impressive results across cross-modal un
arXiv:2605.10242v1 Announce Type: cross Abstract: Unsupervised tabular anomaly detection methods typically learn feature patterns from normal samples during training and subsequently identify samples
arXiv:2604.02564v2 Announce Type: replace-cross Abstract: We present MaskGen, a theoretically grounded and deliberately simple approach for domain generalization in 3D biomedical image segmentation. M
World models recently made our list of 10 Things That Matter in AI Right Now. Watch executive editor Niall Firth explain why this emerging area of AI is gaining so much attention. Join MIT Technology
arXiv:2605.09789v1 Announce Type: new Abstract: Dexterous manipulation is physics-intensive and highly sensitive to modeling errors and perception noise, making sim-to-real transfer prohibitively chal
arXiv:2310.15288v3 Announce Type: replace Abstract: Reward learning techniques enable machine learning systems to learn objectives from human feedback. A core limitation of these systems is their assu
Amazon Quick helps turn your large enterprise data into fast and accurate AI-powered decisions. In this post, you will learn about five new capabilities of Amazon Quick that accelerate how data profes
arXiv:2511.09016v2 Announce Type: replace-cross Abstract: The Kalman filter and Rauch-Tung-Striebel (RTS) smoother are optimal for state estimation in linear dynamic systems. With nonlinear systems, t
arXiv:2605.07034v1 Announce Type: cross Abstract: Modern cybersecurity relies heavily on static machine-learning-based malware classifiers. However, transformations such as packing and other non-seman
arXiv:2605.07277v1 Announce Type: cross Abstract: Many scientific and combinatorial problems admit multiple correct solutions, not a single label. Standard supervised learning resolves this ambiguity
arXiv:2605.06969v1 Announce Type: new Abstract: Infrared-Visible image fusion (IVIF) aims to integrate thermal information and detailed spatial structures into a single fused image to enhance percepti
In this post, you will learn how to set up the Exa integration in Strands Agents, understand the two core tools it exposes, and walk through real-world use cases that show how agents use web search to
arXiv:2605.07886v1 Announce Type: cross Abstract: Online learning from a stream of data is a defining feature of intelligence, yet modern machine learning systems often struggle in this setting, espec
arXiv:2605.07119v1 Announce Type: cross Abstract: Classical clustering methods usually return either a finite partition of the observed data or a finite dendrogram over it. This finite-sample view is
arXiv:2605.08077v1 Announce Type: new Abstract: Knowledge Graph Question Answering (KGQA) has shown promise for grounded and interpretable reasoning, yet existing approaches often fail to provide reli
Cursor is an AI-powered code editor that analyzes entire conversation threads to understand context before generating solutions and automatically creating pull requests for team review. This feature s
arXiv:2605.07940v1 Announce Type: new Abstract: Exemplar-based image editing applies a transformation defined by a source-target image pair to a new query image. Existing methods rely on a pair-of-pai
Sarah Perez / TechCrunch: Digg relaunches as an aggregator of AI news and social media commentary, with plans to expand to other topics; its previous reboot shut down in March — Digg is back from the
Cursor AI has rolled out effort levels functionality to all users on usage-based Bugbot plans, allowing users to configure these settings directly through their Bugbot dashboard. This feature enables
arXiv:2605.08073v1 Announce Type: cross Abstract: Recent event-based image reconstruction methods predominantly rely on Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) to process c
arXiv:2605.07097v1 Announce Type: cross Abstract: We show that, in a precise sense, a broad class of feedforward neural networks learn (have finite sample complexity) in the PAC model: every fixed fin
Explore the beginner's guide to ComfyHub. ComfyHub is the public home for community-built workflows and apps — the fastest way to find and run what the ComfyUI ecosystem has already created, without n
arXiv:2510.01510v3 Announce Type: replace Abstract: We study the problem of zero-shot link prediction on knowledge graphs (KGs), which requires models to generalize to novel entities and novel relatio
arXiv:2605.07474v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models hold great promise for general-purpose robotic intelligence, yet scaling up such models is severely bottlenecked b
arXiv:2605.07203v1 Announce Type: new Abstract: Scene change detection methods built on Gaussian splatting universally follow a render-then-compare paradigm: the pre-change scene is rendered into 2D a
arXiv:2605.07933v1 Announce Type: new Abstract: Latent diffusion models offer an attractive alternative to discrete diffusion for non-autoregressive text generation by operating on continuous text rep
arXiv:2508.05803v2 Announce Type: replace Abstract: Human memory is fleeting. As words are processed, the exact wordforms that make up incoming sentences are rapidly lost. Cognitive scientists have lo
arXiv:2506.12362v3 Announce Type: replace-cross Abstract: Inductive link prediction with knowledge hypergraphs is the task of predicting missing hyperedges involving completely novel entities (i.e., n
I'm delighted that @coursera and @udemy have come together as one company to serve learners. Both Coursera and Udemy were founded with the belief that access to high-quality education changes lives. O
arXiv:2605.07491v1 Announce Type: new Abstract: This paper proposes a novel framework for implicit multi-camera system calibration utilizing Gaussian Process (GP) regression. Conventional explicit cal
arXiv:2605.07010v1 Announce Type: new Abstract: Identifying vulnerable transmission lines in power grids before a cascading failure occurs is challenging: existing methods can learn inter-line failure
arXiv:2605.07648v1 Announce Type: new Abstract: Learning parity functions, more general modular addition, is a challenging machine learning task due to its input sensitivity. A recent study substantia
arXiv:2310.02243v2 Announce Type: replace-cross Abstract: We study the problem of learning a local quantum Hamiltonian H given copies of its Gibbs state rho = e^{-eta H}/extrm{tr}(e^{-eta H}) at a kno
arXiv:2605.06676v1 Announce Type: cross Abstract: Long-context inference in Large Language Models (LLMs) is bottlenecked by the linear growth of Key-Value (KV) cache memory. Existing KV cache compress
// LLMs Improving LLMs // Interesting progress the past of couple of weeks around self-improving AI agents. If autoresearch was interesting, you will like this read. (bookmark it) We've been hand-tuni
arXiv:2605.06809v1 Announce Type: new Abstract: Transformers dominate video recognition. They split videos into tokens, and processing them has expensive superlinear computational cost. Yet videos are
arXiv:2602.03797v2 Announce Type: replace Abstract: We present a new paradigm for creating random features to approximate bi-variate functions (in particular, kernels) defined on general manifolds. Th
arXiv:2605.06317v2 Announce Type: replace-cross Abstract: Existing Vision-Language Navigation (VLN) methods typically adopt an egocentric, step-by-step paradigm, which struggles with error accumulatio
arXiv:2605.07140v1 Announce Type: cross Abstract: Skeleton-based human activity recognition has achieved strong empirical performance, yet most existing models remain black boxes and difficult to inte
arXiv:2605.07660v1 Announce Type: new Abstract: Reinforcement-learning-based post-training has become a key approach for improving the reasoning ability of large language models, but its token-level l
arXiv:2605.06873v1 Announce Type: cross Abstract: Probabilistic conditioning is concerned with the identification of a distribution of a random variable X given a random variable Y. It is a cornerston
arXiv:2605.07572v1 Announce Type: new Abstract: When applying Bayesian optimization (BO) to scientific workflow, a major yet often overlooked source of uncertainty is the task itself -- namely, what t
arXiv:2605.06833v1 Announce Type: cross Abstract: Misbehavior detection in Vehicle-to-Everything (V2X) networks is a second line of defense against insider falsification attacks that cryptographic mec
arXiv:2602.03490v2 Announce Type: replace Abstract: Adaptive cognition requires structured internal models of objects and their relations. Predictive neural networks are often proposed to learn such w
arXiv:2605.08035v1 Announce Type: cross Abstract: Building a site-specific propagation model typically requires either ray-tracing over detailed 3D maps or dense measurement campaigns. Both approaches
arXiv:2605.07938v1 Announce Type: new Abstract: Single-cell representation learning (SCRL) from gene expression data offers a way to uncover the complex regulatory logic underlying cellular function.
arXiv:2605.07755v1 Announce Type: cross Abstract: The theory of state tracking in recurrent architectures has predominantly focused on expressive capacity: whether a fixed architecture can theoretical
arXiv:2605.07212v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a cornerstone of brain-computer interfaces and clinical neuroscience, yet deep learning models are typically trained a
This tutorial demonstrates how to implement full-text search functionality using Pinecone's vector database, using bird-related data as a practical example. It likely covers setting up Pinecone, index
arXiv:2602.03201v3 Announce Type: replace Abstract: Model-based reinforcement learning (MBRL) is sample-efficient but struggles in sparse reward settings. A critical bottleneck arises from the lack of
arXiv:2605.07908v1 Announce Type: cross Abstract: Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack