Knowledge catalogue
arXiv:2607.01012v1 Announce Type: new Abstract: Data assimilation models state dynamics conditioned on sequential observations, and has wide-ranging scientific applications. In the filtering setting,
arXiv:2607.00301v1 Announce Type: new Abstract: The emergence of powerful deep generative models based on diffusion and flow matching has enabled the learning and modeling of complex distributions. Le
arXiv:2607.00492v1 Announce Type: new Abstract: We introduce GenSP, a data-driven framework that learns consistent spherical parameterizations across a collection of genus-0 shapes. Instead of optimiz
arXiv:2602.03082v2 Announce Type: replace Abstract: A growing number of neural architectures have been proposed to enforce geometric constraints, including projection-based networks, exponential-map u
arXiv:2607.00083v1 Announce Type: cross Abstract: Language models have changed from unreliable text generators to highly-capable large models with trillions of parameters. Capability increases come ha
Hot take: I think it's still important to understand the code that our agents write! In this mega thread (based on my AIE talk today), I will explain why that's the case, and show some ideas for how t
huge week of really exciting launches at langchain! big week at langchain, with a lot of launches: 1/ OpenWiki - auto generate a wiki of a github repo 2/ two different voice agent tutorials 3/ Harbor
arXiv:2403.19645v2 Announce Type: replace Abstract: The rapid advancement of diffusion models has enabled the generation of high-fidelity images from textual prompts, yet achieving precise, disentangl
arXiv:2607.00955v1 Announce Type: cross Abstract: Implicit neural representations (INRs) are well suited to cardiac motion estimation, providing continuous, compact representations of motion fields. H
arXiv:2602.23164v2 Announce Type: replace Abstract: Foundation models must handle multiple generative processes, yet mechanistic interpretability largely studies capabilities in isolation; it remains
arXiv:2607.01124v1 Announce Type: cross Abstract: Muon has recently emerged as one of the most effective optimizers for training large neural networks, yet its empirical success has been explained fro
New research from Google. LLMs hallucinate with high confidence, miss their own knowledge boundaries, and misreport uncertainty. Most fixes bolt calibration on from the outside. RLMF turns the model o
Obvious in retrospect, but I didn't really anticipate: Fable: Performing Final Review of <Awesome Feature> Also Fable: I appear to have introduced a critical security vulnerability. <This model's safe
arXiv:2607.00586v1 Announce Type: cross Abstract: We present a simple, yet general approach to study the scaling properties as the dimensionality of Metropolised MCMC sampling algorithms increases. Th
Our goal is to help security teams shift from reactive triage to proactively fixing what matters, close the critical gaps scanners miss before they become breaches, and return engineering capacity to
arXiv:2607.00522v1 Announce Type: new Abstract: Restoring incomplete or damaged 3D objects is crucial for cultural heritage preservation, occluded object reconstruction, and artistic design. Existing
arXiv:2607.00714v1 Announce Type: cross Abstract: Self-conditioning is a core technique that enhances continuous flow-based language models, where the model learns to denoise generated text by conditi
arXiv:2509.22557v3 Announce Type: replace Abstract: Mixed bundle pricing is a classic revenue management problem arising in industries such as e-commerce, tourism, and video games. It refers to design
arXiv:2607.01105v1 Announce Type: new Abstract: We present SynLaD, a latent diffusion framework for small-molecule generation that unifies ligand-based drug design objectives (what to make) with synth
arXiv:2607.00849v1 Announce Type: new Abstract: News articles are an important source of information on disaster impacts and adaptation. A key methodological challenge in socio-environmental studies i
In this post, we demonstrate how to deploy BoltzGen on SageMaker AI and run an end-to-end protein design experiment. By the end of the walkthrough, you have a working setup that scales from quick vali
arXiv:2606.31069v1 Announce Type: new Abstract: Up to this point, keyword extraction task typically relies solely on textual data. Neglecting visual details and audio features from image and audio mod
arXiv:2606.31275v1 Announce Type: cross Abstract: Online Continual Self-Supervised Learning (OCSSL) aims to learn representations from a continuous stream of unlabeled data, without knowledge of task
arXiv:2606.31909v1 Announce Type: new Abstract: In this work, we study Compositional Dexterous Functional Object Manipulation (CD-FOM): tasks such as aiming and actuating a spray bottle on a plant or
arXiv:2606.15305v2 Announce Type: replace Abstract: Accurate brain tumor segmentation from multiparametric magnetic resonance imaging (MRI) is critical for treatment planning, response assessment, and
arXiv:2510.09340v2 Announce Type: replace Abstract: Recent language models exhibit significant logical reasoning abilities, yet the mechanisms supporting deductive inference remain poorly understood.
Trq212 is presenting a Field Guide to Fable at AI.Engineer World's Fair, indicating renewed interest or development in the Fable project or framework. This presentation likely covers Fable's features,
arXiv:2606.32016v1 Announce Type: new Abstract: Multimodal graph foundation models aim to learn reusable knowledge from graphs enriched with text, images, attributes, and relational topology, thereby
arXiv:2512.04390v2 Announce Type: replace-cross Abstract: Joint video super-resolution and deblurring (VSRDB) requires both efficient long-range temporal modeling and robustness to frame-wise exposure
At Google Cloud, we are committed to providing public sector organizations around the globe with cloud technology that is highly flexible, scalable, and built with market-leading standards for data pr
Great talk by @trq212 ! You mentioned you generated the slides in 4 hours with Fable? These slides were gorgeous!! Most other presenters using AI generated deck look horrible. Can you please share any
In this post, we demonstrate how to implement HippoRAG using a comprehensive AWS stack. We use Amazon Bedrock for LLM capabilities, Amazon Neptune for graph database functionality, Amazon Neptune Anal
arXiv:2606.32009v1 Announce Type: new Abstract: Vision-language-action (VLA) models across robot embodiments require high-quality observation--action supervision to learn deployable action distributio
This Replit post likely provides a security walkthrough covering four essential security considerations for developers building applications on the Replit platform. The guide appears aimed at app buil
arXiv:2505.18521v2 Announce Type: replace Abstract: The substantial training cost of diffusion models hinders their deployment. Immiscible Diffusion recently showed that reducing diffusion trajectory
arXiv:2606.31924v1 Announce Type: new Abstract: Controllable image generation methods, such as ControlNet, have demonstrated a remarkable capacity to introduce visual conditions(e.g., depth maps) to g
Interrupt 2026 is coming to New York City and London this fall. → Hear from engineers + teams shipping agents in production → Keynotes from @hwchase17 + industry leaders on what's next for agents → Ha
arXiv:2606.31637v1 Announce Type: cross Abstract: Intrinsic decomposition which expresses image colors as the product of diffuse albedo and shading, possibly augmented with view-dependent residuals ha
arXiv:2606.32038v1 Announce Type: cross Abstract: When does training language models (LMs) to generate explanations of their predictions yield faithful introspection, rather than superficial imitation
Just published a YouTube video walking through OpenWiki. Setup and configuration, how it works, what it targets, and how to automatically keep your docs up to date. Check it out, and see the OSS GitHu
arXiv:2601.22123v4 Announce Type: replace Abstract: Simulating the long-time evolution of Hamiltonian systems is limited by the small timesteps required for stable numerical integration. To overcome t
arXiv:2606.31856v1 Announce Type: new Abstract: We study layered models, including feedforward networks, ResNets, and transformers, by limiting each layer to a width of d = 3, i.e., R^3 as representat
More and more developers turning to glm5.2 as a daily driver for coding Here’s how to use it with deepagents code You can start building with GLM 5.2 in minutes: 1️⃣ Download dcode 2️⃣ Select your mod
arXiv:2603.13748v3 Announce Type: replace Abstract: Real-world robots often operate in settings where objective priorities depend on the underlying context of operation. When the underlying context is
arXiv:2606.31919v1 Announce Type: cross Abstract: Zero-shot Object Goal Navigation (ZSON) with RGB-only perception poses a fundamental challenge for embodied agents, as the absence of explicit depth i
Security leaders are now expected to protect business growth and clearly articulate security value to their board of directors, in addition to managing risk. While translating technical defense into m
arXiv:2606.31703v1 Announce Type: new Abstract: Face-swapping deepfakes pose an escalating threat to personal privacy by enabling unauthorized identity manipulation. While adversarial approaches have
arXiv:2606.32036v1 Announce Type: new Abstract: Producing 3D human representations from input views on the fly is essential for immersive live streaming systems, where representation compactness is as
This video provides a quick explanation of Retrieval-Augmented Generation Models (RLMs), outlining their benefits and demonstrating their implementation with DeepAgents. The content likely covers how
arXiv:2506.23102v2 Announce Type: replace-cross Abstract: Current CT report generation frameworks predominantly rely on global feature representations, often failing to capture region-specific details
The Amazon Bedrock Model Profiler is an open source tool that aggregates model metadata from multiple AWS APIs and external sources into a single, searchable interface. In this post, you’ll learn what
arXiv:2506.20995v4 Announce Type: replace Abstract: We propose a step-by-step video-to-audio (V2A) generation method that provides finer control over the generation process and more realistic audio sy
tmrw at @aidotengineer i’ll be exploring history’s most beautiful and fertile minds. i’m calling it Imagination Engineering. i’ve been asking myself how to become an idea factory, as originality becom
arXiv:2606.30655v1 Announce Type: cross Abstract: AI-native course assessments in senior computer science courses and related fields should grade students by AI-resilient skill: the ability to achieve
arXiv:2606.30696v1 Announce Type: cross Abstract: Enabling robots to follow natural language commands to complete zero-shot long-horizon tasks remains challenging. It requires extracting implicit temp
arXiv:2606.31946v1 Announce Type: new Abstract: The fundamental obstacle to industrial grade video generation is the lack of controllability: existing models treat video as a pixel distribution sampli
arXiv:2002.11508v3 Announce Type: replace Abstract: TCSPs (Temporal Constraint Satisfaction Problems) [Dechter et al. 1991] get rid of unary constraints by binarizing them after having added an 'origi
arXiv:2606.30230v1 Announce Type: cross Abstract: Learned reconstruction operators for inverse problems are typically trained under a fixed noise model, and generalize poorly when the distribution dur
arXiv:2509.20848v2 Announce Type: replace-cross Abstract: In the classic point location problem, one is given an arbitrary dataset X subset R^d of n points with query access to an unknown halfspace f
arXiv:2606.30217v1 Announce Type: new Abstract: Large multimodal models have achieved strong reasoning on complex visual tasks, but their inference efficiency is often restricted by long chains of tho