Knowledge catalogue
arXiv:2604.23623v1 Announce Type: new Abstract: Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit st
arXiv:2604.22951v1 Announce Type: new Abstract: Natural language data follows a power-law distribution, with most knowledge and skills appearing at very low frequency. While a common intuition suggest
This year's AI Accelerator winners shipped agents for finance teams, application security, and real estate. They built with $8M in credits and hands-on mentorship from Vercel, @awscloud, @OpenAI, @Ant
arXiv:2602.19019v2 Announce Type: replace Abstract: Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without a
arXiv:2312.08410v5 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel
What's new in pip 26.1 - lockfiles and dependency cooldowns! Richard Si describes an excellent set of upgrades to Python's default pip tool for installing dependencies. This version drops support for
arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s
arXiv:2604.23709v1 Announce Type: new Abstract: Single image dehazing is often constrained by a trade-off between restoration quality and computational efficiency. While efficient, CNN networks strugg
arXiv:2604.22557v1 Announce Type: cross Abstract: The emergence of large-scale pretrained foundation models has transformed computer vision, enabling strong performance across diverse downstream tasks
At #ICLR? Don’t miss @realDanFu 👇 Latent & Implicit Thinking Workshop (LIT) 🕐 Workshop at 1:30 PM BRT (local) Exploring what comes after chain-of-thought and how models may actually reason. 🔗 https://
Amazon Quick Flows enables users to build automations for repetitive or routine tasks using simple, everyday language prompts , with no technical expertise required. The service uses an AI-powered UI
arXiv:2604.22618v1 Announce Type: new Abstract: Self-supervised learning in healthcare has largely relied on invariance-based objectives, which maximize similarity between different views of the same
arXiv:2604.22636v1 Announce Type: cross Abstract: Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual sett
arXiv:2512.20831v2 Announce Type: replace Abstract: Real-world sequential decision-making often involves parameterized action spaces that require both, decisions regarding discrete actions and decisio
arXiv:2604.22529v1 Announce Type: new Abstract: Self-supervised learning has achieved remarkable success in learning visual representations from clean data, yet remains challenging when clean observat
arXiv:2603.24350v2 Announce Type: replace-cross Abstract: A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a 'sel
arXiv:2604.22724v1 Announce Type: new Abstract: Imitation learning is a well-established approach for machine-learning-based control. However, its applicability depends on having access to demonstrati
arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th
This article likely discusses techniques for building web applications that integrate OpenAI's APIs while maintaining user privacy through filtering mechanisms. It probably covers implementation strat
It just takes a little time and care to engage with the work of new folks in the field -- but it can make a big difference :D On a more personal note, I'm grateful to @jeremyphoward for helping me bre
arXiv:2601.11719v3 Announce Type: replace Abstract: Self-supervised learning, in the context of foundation model training, is a powerful pre-training method for learning feature representations withou
Google and Kaggle are offering a free five-day AI Agents Intensive course running June 15–19, 2026. The course teaches 'vibe coding' to create programs using natural language, with hands-on projects t
last week we dropped a super comprehensive guide on runtime requirements for long running agents! this week i'll be diving into each requirement and runtime capability that meets it, here's the lineup
arXiv:2604.22212v1 Announce Type: cross Abstract: In spite of the utility of 3-D electron back-scattered diffraction (EBSD) microscopy, the data collection process can be time-consuming with serial-se
arXiv:2604.22354v1 Announce Type: new Abstract: Each scanner possesses its unique characteristics and exhibits its distinct sampling error distribution. Training a network on a dataset that includes d
arXiv:2604.22658v1 Announce Type: new Abstract: Single-view 3D shape retrieval is a fundamental yet challenging task that is increasingly important with the growth of available 3D data. Existing appro
arXiv:2604.22385v1 Announce Type: cross Abstract: Rejection sampling is a technique for sampling from difficult distributions. However, its use is limited due to a high rejection rate. Common adaptive
arXiv:2506.07298v3 Announce Type: replace-cross Abstract: Hidden Markov Models (HMMs) are foundational tools for modeling sequential data with latent Markovian structure, yet fitting them to real-worl
arXiv:2604.22157v1 Announce Type: cross Abstract: Existing research typically treats privacy policies as flat, uniform text, extracting information without regard for the document's logical hierarchy.
arXiv:2604.22649v1 Announce Type: cross Abstract: Objective: Decoding visual information from electroencephalography (EEG) is an important problem in neuroscience and brain-computer interface (BCI) re
the difference is that we don’t *hype* giving 12 year-olds bulldozers. *of course* it’s a kind of user error when a model destroys all of user’s data and they didn’t have a backup. that’s the point. v
arXiv:2604.22579v1 Announce Type: cross Abstract: We study whether deep networks for medical imaging learn useful nonrobust features - predictive input patterns that are not human interpretable and hi
“AI: it feels most impressive when you don’t know much about the subject, don’t care or don’t have a clear idea of what the you want… Once you know what something should feel or look like, it becomes
ChatGPT's GPT Image 2 is actually incredible. Full visual breakdown of how to fix my desk setup. I refuse to get rid of my second monitor (I need 3 for live zoom client workshops), but this was the ki
Fieri Iussit https://x.com/emollick/status/1969993499157446943?s=20 My modest proposal for how to acknowledge AI work is to use the Latin phase 'Fieri Iussit,' which means 'commanded to be made,' a co
OpenAI's core principles outline the company's commitment to developing artificial intelligence safely and beneficially, emphasizing responsible AI development and deployment. These principles likely
Great paper on improving proactive agents. (bookmark it) Proactive agents act before you do. But how do you evaluate something that's supposed to anticipate needs you haven't expressed? This work intr
This guide addresses updated regulatory requirements for model risk management in banking institutions, likely covering the 2026 revisions to interagency guidance issued by banking regulators. It prov
There's still time to submit. The applications coming in are pretty good, the bar is high. Two weeks to pitch a show you wish existed. $100K in cash prizes. Bring your biggest, most ambitious ideas to
arXiv:2509.03294v3 Announce Type: replace-cross Abstract: The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurit
arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin
arXiv:2604.20862v1 Announce Type: new Abstract: The automation system for Course of Action (CoA) planning is an essential element in future warfare. As maneuver speeds increase, surveillance ranges ex
arXiv:2305.01626v4 Announce Type: replace-cross Abstract: Computational models of syntax are predominantly text-based. Here we propose that the most basic first step in the evolution of syntax can be
arXiv:2604.20893v1 Announce Type: new Abstract: Wrist exoskeletons play a vital role in rehabilitation and assistive applications, yet conventional actuation mechanisms such as electric motors or pneu
arXiv:2604.21631v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) achieves real-time photorealistic rendering, its performance degrades significantly when training images contain tran
arXiv:2604.21300v1 Announce Type: new Abstract: Learning robust representations of authorial style is crucial for authorship attribution and AI-generated text detection. However, existing methods ofte
arXiv:2410.16006v3 Announce Type: replace Abstract: A common challenge towards the adaptability of Large Language Models (LLMs) is their ability to learn new languages over time without hampering the
arXiv:2604.21175v1 Announce Type: new Abstract: We propose a learning-augmented framework for accelerating max-flow computation and image segmentation by integrating Graph Neural Networks (GNNs) with
arXiv:2502.20769v3 Announce Type: replace Abstract: Developing interpretable models for neurodevelopmental disorders (NDDs) diagnosis presents significant challenges in effectively encoding, decoding,
arXiv:2604.21046v1 Announce Type: new Abstract: Semi-supervised learning has emerged as a powerful paradigm for leveraging large amounts of unlabeled data to improve the performance of machine learnin
arXiv:2604.21351v1 Announce Type: new Abstract: The integration of imitation and reinforcement learning has enabled remarkable advances in humanoid whole-body control, facilitating diverse human-like
arXiv:2510.04548v2 Announce Type: replace-cross Abstract: In-context learning (ICL) is a key building block of modern large language models, yet its theoretical mechanisms remain poorly understood. It
arXiv:2604.21097v1 Announce Type: cross Abstract: Chaos arises in many complex dynamical systems, from weather to power grids, but is difficult to accurately model using data-driven emulators, includi
arXiv:2604.20858v1 Announce Type: cross Abstract: Sequential recommendation has rapidly advanced in click-through rate prediction due to its ability to model dynamic user interests. A key challenge, h
arXiv:2604.21100v1 Announce Type: new Abstract: To address the increasing long-context compute limitations of softmax attention, several subquadratic recurrent operators have been developed. This work
arXiv:2604.21765v1 Announce Type: new Abstract: Data is a central resource for modern enterprises, and data validation is essential for ensuring the reliability of downstream applications. However, ex
arXiv:2604.21776v1 Announce Type: new Abstract: Precise camera control for reshooting dynamic videos is bottlenecked by the severe scarcity of paired multi-view data for non-rigid scenes. We overcome
arXiv:2604.21409v1 Announce Type: new Abstract: We present S1-VL, a multimodal reasoning model for scientific domains that natively supports two complementary reasoning paradigms: Scientific Reasoning
arXiv:2604.21681v1 Announce Type: new Abstract: We present Sapiens2, a model family of high-resolution transformers for human-centric vision focused on generalization, versatility, and high-fidelity o
Sapiens2 is the highest quality ViT backbone that now exists in the public domain. It was pretrained on the equivalent of 1/2 of all human images on Flickr. First public release by a large lab that is