Knowledge catalogue
Two 15-year-old boys were detained after they were caught drinking and shooting water beads from a toy gun while riding in a San Mateo driverless Waymo, which remotely halted and locked the doors afte
We are excited to launch 𝗥𝗲𝘀𝘁𝗮𝘁𝗲 𝗕𝗬𝗢𝗖 (Bring-your-own-Cloud) today. It is fully managed @restatedev, with all the features of Restate Cloud, but in your own account, in a dedicated VPC. Data never lea
We’ve made improvements to the FrontierCode methodology and are releasing FrontierCode 1.1 with clearer guidelines for fair internet use and refined grading criteria. Learn more about the changes on o
arXiv:2607.06234v1 Announce Type: new Abstract: Generating CT volumes from MRI and CBCT can improve treatment planning in adaptive radiotherapy while avoiding additional radiation exposure. However, d
arXiv:2607.06438v1 Announce Type: cross Abstract: Retargeting human object interaction demonstrations to physics based simulation requires reproducing not only body motion but also the object motion a
arXiv:2607.03298v1 Announce Type: cross Abstract: Foundation models for Earth systems have so far been trained primarily on physical climate and weather data, with limited representation of the human
This article from Latent Space provides an overview of Fable, covering its capabilities, architecture, or use cases as an AI model or framework. The guide likely serves as a reference resource for dev
arXiv:2607.02699v1 Announce Type: new Abstract: The object detection in satellite imagery has garnered considerable attention due to its extensive real-world applications and the inherent challenges i
ARC Prize 2026: ARC-AGI-3 Milestone #1 Winners Congratulations to the three winners who open-sourced their top-scoring ARC-AGI-3 solutions: 1. @tufalabs - 1.21%, 25K 2. Reki - .867%, 7.5K 3. Md Boktia
arXiv:2607.04145v1 Announce Type: cross Abstract: Adversarial attacks guide and provide additional training and test data for both adversarial training and adversarial robustness validation, and expos
arXiv:2607.03018v1 Announce Type: new Abstract: Active Speaker Detection determines whether a visible person in a video is speaking at each moment. While recent audio-visual fusion methods perform wel
arXiv:2607.05000v1 Announce Type: cross Abstract: Canonical quantization provides a systematic procedure for constructing quantum models from classical Hamiltonians. Here, we apply this principle to a
arXiv:2607.05046v1 Announce Type: new Abstract: Evaluating generative AI models is a routine, but resource-intensive, process that is conducted over and over again during the course of model developme
arXiv:2607.02622v1 Announce Type: cross Abstract: Multiplex CRISPR-Cas9 gene editing requires selecting one guide RNA per target gene subject to cross-gene interactions: a constrained combinatorial pr
arXiv:2607.04572v1 Announce Type: new Abstract: Large language model (LLM) tutors often produce fluent step-by-step explanations, but a correct and pedagogically formatted response does not guarantee
arXiv:2607.04779v1 Announce Type: new Abstract: Reasoning segmentation aims to predict pixel-wise masks for targets given complex language queries. Existing approaches leverage Multimodal Large Langua
arXiv:2607.02718v1 Announce Type: cross Abstract: Recent advances in large-scale image generative models enable photorealistic scene synthesis with controllable attributes. Beyond data augmentation, t
arXiv:2202.14019v3 Announce Type: replace-cross Abstract: Maintaining proper form while exercising is important for preventing injuries and maximizing muscle mass gains. Detecting errors in workout fo
arXiv:2503.10954v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents can solve *any* computational problem *without* an algorithm in a runtime *independent* of the computational
arXiv:2607.04276v1 Announce Type: new Abstract: Diffusion models achieve impressive image-generation quality but remain expensive at inference time. Diffusion distillation reduces sampling steps, yet
In this post, we walk through what Dataset Enrichment is, how it differs from legacy Topics, and provide three migration scenarios with step-by-step guidance so you can move your business context into
If you're struggling to get started with evals, you're not alone. This post explains how to write LLM evals as ordinary tests in CI with Phoenix, pytest, and Vitest/Jest. The post Evals in CI: How to
arXiv:2607.02854v1 Announce Type: cross Abstract: Before fixing an issue, it is useful to first reproduce it by generating a bug reproduction test (BRT). However, generating a BRT is itself a challeng
arXiv:2503.10496v2 Announce Type: replace-cross Abstract: Modeling natural phenomena with artificial neural networks (ANNs) often provides highly accurate predictions. However, ANNs often suffer from
arXiv:2508.16771v3 Announce Type: replace-cross Abstract: Code Language Models (CodeLLMs) learn token importance from data correlations, whereas human developers attend selectively to semantically sal
arXiv:2512.16357v3 Announce Type: replace Abstract: Pre-trained Latent Diffusion Models (LDMs) have recently shown strong perceptual priors for low-level vision tasks, making them a promising directio
arXiv:2607.03330v1 Announce Type: new Abstract: Quantifying plant growth dynamics from sparse longitudinal 3D observations is fundamental for agriculture and plant sciences. Yet, plants pose unique ch
Hello, my dear friends, we have some breaking news today! Our rentosertib (novel target that has never been in clinical trials before we picked it using AI, novel molecule designed using true generati
ComfyUI shared a blog post link via their @hellorob account offering additional learning resources about their platform or features. The tweet directs users to their blog through a shortened URL for m
arXiv:2607.02038v2 Announce Type: replace Abstract: The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious
arXiv:2607.04709v1 Announce Type: cross Abstract: Modern machine learning systems demand extensive datasets for visual recognition. Conversely, humans learn with high efficiency despite severe data li
arXiv:2607.05329v1 Announce Type: new Abstract: Siamese verification networks are widely used to compare items such as faces, cars, or signatures. In these scenarios, the network is trained to learn a
arXiv:2607.05316v1 Announce Type: new Abstract: Large language models generate one token at a time, yet their responses show remarkably consistent length structure: step-by-step solutions converge in
arXiv:2607.04341v1 Announce Type: cross Abstract: This state-of-the-art report provides an overview of controllable 3D human avatar creation. We describe current 3D avatar systems, which typically con
arXiv:2603.24025v2 Announce Type: replace Abstract: Unsupervised learning of high-dimensional data is challenging due to irrelevant or noisy features obscuring underlying structures. It's common that
arXiv:2602.19143v2 Announce Type: replace Abstract: This paper studies simple transformers trained on a high-order Markov chain, where the model must incorporate information from multiple past positio
arXiv:2607.02800v1 Announce Type: new Abstract: Induction heads are attention circuits believed to underlie in-context learning in transformers, yet a precise characterization of the estimators they i
arXiv:2506.21887v2 Announce Type: replace Abstract: High-stakes decision-making involves navigating multiple competing objectives with expensive evaluations. For instance, in brachytherapy, clinicians
arXiv:2607.04156v1 Announce Type: new Abstract: Scientific equation discovery must combine broad domain priors with strict numerical testing. Symbolic regression supplies numerical grounding but faces
arXiv:2607.05263v1 Announce Type: new Abstract: This paper concerns the problem of unsupervised temporal action segmentation for long, untrimmed videos. Recent successful approaches follow a joint rep
arXiv:2607.04711v1 Announce Type: new Abstract: Continual learning aims to progressively learn from a sequence of tasks, each containing a disjoint subset of classes, while preserving previously learn
arXiv:2401.10805v4 Announce Type: replace-cross Abstract: We introduce the novel concept of visually Connecting Actions and Their Effects (CATE) in video understanding. CATE can have applications in a
arXiv:2503.18509v2 Announce Type: replace Abstract: Weak supervision enables machine learning models to learn from limited or noisy labels, but it introduces challenges in reliability and semantic cla
🎓 New course launch from LangChain Academy: Introduction to Deep Agents ✅ Learn what a harness is, and why agents need one ✅ Understand the 4 core capabilities of a harness ✅ Start building with Deep
Now I'm regretting having carefully blasted through 100% of my Fable allotment in time for being cut off at the end of today! (Presumably 'Wed 12:00 PM' means I get it back at noon on Wednesday, not a
arXiv:2603.19954v2 Announce Type: replace Abstract: Transformers have shown inconsistent success in AI planning tasks, and theoretical understanding of when generalization should be expected has been
arXiv:2607.04118v1 Announce Type: cross Abstract: With the rise of parametric memory, LoRA-based External Parametric Memory (EPM) has emerged as a modular solution, but existing routing methods often
arXiv:2607.05127v1 Announce Type: cross Abstract: Understanding the physics of many-body complex dynamical systems is typically non-trivial. High-dimensional analysis approaches are often deemed neces
arXiv:2607.04587v1 Announce Type: new Abstract: Robust 3D object detection in adverse weather conditions is challenging due to sensor limitations. Although combining complementary modalities such as L
arXiv:2607.03303v1 Announce Type: new Abstract: While Large Language Models (LLMs) can provide personalized support in learning, several studies have raised concerns regarding their use in education.
arXiv:2607.03640v1 Announce Type: cross Abstract: Fine-tuning can give a language model a hidden behavior--it may give false answers under a narrow condition, or give harmful advice only when a prompt
arXiv:2510.19698v3 Announce Type: replace Abstract: Large Language Models (LLMs) can propose rules in natural language, sidestepping the need for a predefined predicate space in traditional rule learn
arXiv:2607.03196v1 Announce Type: new Abstract: WiFi-based human pose estimation (HPE) enables the detection and interpretation of human body positions and movements without the need for wearable devi
arXiv:2607.02402v2 Announce Type: replace Abstract: Vision-language models (VLMs) can follow complex textual instructions, yet they struggle to reason from purely visual context. In particular, curren
arXiv:2607.04064v1 Announce Type: cross Abstract: Unsupervised syllabic tokenization aims to learn discrete syllabic tokens that capture latent linguistic content-related structure from raw speech. Re
tldr of thariq's AIEWF keynote https://latent.space/p/ainews-the-field-guide-to-fable (more in today's ainews issue) my keynote at AI Engineer World Fair: “A Field Guide to Fable” is live on YouTube!
arXiv:2502.12096v5 Announce Type: replace-cross Abstract: In this paper, we introduce token communications (TokCom), a large model-driven framework to leverage cross-modal context information in gener
arXiv:2607.02864v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a powerful approach in financial trading, enabling agents to learn optimal strategies through direct market i
arXiv:2607.04969v1 Announce Type: cross Abstract: The training paradigm of large language models has shifted from traditional one-pass training to multi-epoch training, as reasonable reuse of limited
arXiv:2603.07606v2 Announce Type: replace Abstract: Interpretable machine learning is essential in high-stakes domains where decision-making requires accountability, transparency, and trust. While rul