Knowledge catalogue
In June, the Tesla Model Y became the best-selling vehicle overall in New Zealand, surpassing all other car models in monthly sales. This announcement was shared by Elon Musk on X (formerly Twitter),
arXiv:2607.01171v1 Announce Type: new Abstract: Sample-based generative models are increasingly used for probabilistic forecasting in high-stakes decision settings, yet their training objectives are b
Model Y long wheelbase now available to order in the US Introducing Model Y Long Wheelbase – now available in the US & Puerto Rico A 3-row, 6-seat configuration that brings exceptional interior space
arXiv:2607.00569v1 Announce Type: new Abstract: In this article, we present dynamic modeling, gait synthesis, and feedback control design for a modular novel subsurface robot, designed for human-free
Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to purely autoregressive language models because they can decode multiple tokens in parallel. However, state-of-the-art
arXiv:2607.00170v1 Announce Type: cross Abstract: Thermodynamic computing devices based on the Ising model show great promise for low-power AI inference and edge computing, but scalable methods for tr
arXiv:2607.01166v1 Announce Type: cross Abstract: Video predictive models are emerging as a powerful paradigm in robotics, offering a promising path toward task generalization, long-horizon planning,
AlloyDB is an AI-native database—it isn’t just a passive data store, it intelligently understands and processes your data. With AlloyDB, you get industry-leading vector and hybrid search, near 100% ac
arXiv:2606.19100v2 Announce Type: replace Abstract: Large Vision and Language Models (LVLMs) have advanced rapidly, yet European Portuguese (pt-PT) remains systematically underserved by existing open-
arXiv:2606.31232v1 Announce Type: new Abstract: Learning visual world models for planning requires compact latent dynamics that remain sensitive to actions, yet reconstruction-free joint-embedding obj
arXiv:2601.13932v2 Announce Type: replace-cross Abstract: Reaching consensus on massive discussion networks is critical for reducing noise and achieving optimal collective outcomes. However, the natur
arXiv:2606.31814v1 Announce Type: new Abstract: Lane topology reasoning aims to construct a lane graph from onboard sensor observations. Existing methods follow a detection and association paradigm th
get started with deep agents code, our open source coding agent with first class open model support You can start building with GLM 5.2 in minutes: 1️⃣ Download dcode 2️⃣ Select your model (GLM 5.2) 3
arXiv:2606.31889v1 Announce Type: new Abstract: This paper presents a novel non-linear mathematical model of an articulated tractor-trailer system that can be used, in combination with receding horizo
arXiv:2502.15637v2 Announce Type: replace-cross Abstract: While foundation models have revolutionized various domains, their application to time series classification remains rather under-explored, wi
Open models are the future, and that future starts now GLM 5.2 has become my daily driver. here’s how and why: You can start building with GLM 5.2 in minutes: 1️⃣ Download dcode 2️⃣ Select your model
arXiv:2603.21210v3 Announce Type: replace Abstract: Designing urban spaces that provide pedestrian wind comfort and safety requires time-resolved Computational Fluid Dynamics (CFD) simulations, but th
arXiv:2606.31693v1 Announce Type: cross Abstract: The wave of AI-native applications is moving shopping beyond page- and feed-based browsing toward intent-driven experiences orchestrated by LLM agents
arXiv:2602.23721v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models integrate visual observations and language instructions to predict robot actions, demonstrating promising
arXiv:2602.15029v3 Announce Type: replace-cross Abstract: The internal representations learned by language models consistently exhibit striking geometric structure: calendar months organize into a cir
arXiv:2601.18778v3 Announce Type: replace-cross Abstract: RL methods for scaling large reasoning models stall on datasets with low initial success rates, and thus little training signal. We investigat
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:2606.29212v1 Announce Type: new Abstract: Agent-based evacuation simulations are widely used to study crowd behavior during emergencies, but many models rely on assumptions such as perfect event
A great read from @LangChain Best framing I've seen for agent architecture. Every non-model piece like the filesystem, sandbox, compaction, Ralph loops exists to patch a specific model limitation. htt
A study from @Stanford showed that 71.3% of chatgpt queries could be accurately answered by a local model. I suspect a major part of enterprise AI workloads could be run locally too for free (compared
arXiv:2606.28926v1 Announce Type: cross Abstract: In-context learning (ICL) is an emerging paradigm that employs the semantic information inherent in large language models (LLMs) for generating answer
arXiv:2606.30429v1 Announce Type: new Abstract: Text-to-3D systems can now synthesize a mechanical part from a single sentence, yet the result is a shape to render, not a design to edit. We present Ar
As open models get stronger, more workloads move into the competitive inference market. That pushes the real fight toward speed, cost, reliability, and control. Together AI is where open models become
arXiv:2606.29689v1 Announce Type: new Abstract: Open-ended aesthetic critique is a challenge for multimodal large language models (MLLMs): unlike multiple-choice aesthetic benchmarks, it has no single
arXiv:2512.02453v2 Announce Type: replace Abstract: Existing stylized motion generation models have shown their remarkable ability to understand specific style information from the style motion, and i
arXiv:2606.29495v1 Announce Type: new Abstract: Social influence dialogue changes user behavior by altering internal cognitive states. The central evaluation question is whether the user's beliefs, de
arXiv:2606.28455v1 Announce Type: cross Abstract: World models can predict future physical states, but prediction accuracy alone does not explain how physical information is organized and used inside
arXiv:2606.29384v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become an important paradigm of embodied AI. However, existing VLA models typically assume well-lit and stable
arXiv:2412.08108v3 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable performance on multimodal tasks but remain highly vulnerable to small adversaria
Hugging Face introduced a feature that displays evaluation results from the 'Every Eval Ever' (EEE) community evaluation initiative directly on model pages, providing users with comprehensive benchmar
arXiv:2606.30473v1 Announce Type: cross Abstract: We study retrieval over catalogs of structured metadata, where each record is a small schema whose fields answer different kinds of query. Embedding a
In this post, you'll learn how fine-tuning Amazon Nova models using Amazon SageMaker AI addresses these specific issues by teaching the models to recognize your exact data patterns, distinguish betwee
arXiv:2603.19235v2 Announce Type: replace Abstract: While Multimodal Large Language Models demonstrate impressive semantic capabilities, they often suffer from spatial blindness, struggling with fine-
Google introduced Nano Banana 2 Lite, its fastest and most cost-efficient image model built for high throughput, speed and scale. The model generates text-to-image outputs in about four seconds and co
arXiv:2603.22876v2 Announce Type: replace-cross Abstract: Learning a generalist control policy for robotic manipulation typically relies on large-scale datasets. Given the high cost of real-world data
TabFM is a foundation model designed for tabular data classification and regression that eliminates the need for manual model training, hyperparameter tuning, and complex feature engineering by framin
arXiv:2606.30397v1 Announce Type: cross Abstract: The increasing integration of Electric Vehicles (EVs) has imposed a growing harmonic challenge on the power grid. For AC/DC Power Factor Correction (P
arXiv:2606.28546v1 Announce Type: new Abstract: Recent advances in AI-driven weather and climate modeling have improved forecast skill while reducing computational cost. However, existing data-driven
arXiv:2606.28630v1 Announce Type: new Abstract: Forecasting longitudinal brain lesion evolution is critical for disease monitoring and treatment planning. Existing approaches typically learn a direct
arXiv:2412.19897v3 Announce Type: replace-cross Abstract: We introduce a local surrogate approach for explainable time-series forecasting. An initially non-interpretable predictive model to improve th
arXiv:2606.29799v1 Announce Type: new Abstract: This project introduces the CRISTAL Method (Coherent Reliable Intentional Synthesis of Truthful Analysis Logic), a neurosymbolic framework for automatin
arXiv:2606.29776v1 Announce Type: cross Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is the gold standard for molecular structure elucidation, yet interpreting complex spectra for unknown m
arXiv:2606.29097v1 Announce Type: new Abstract: Recent research has investigated the use of large language models (LLMs) to generate traffic scenarios for autonomous driving. However, pretrained LLMs
arXiv:2601.03546v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to simulate decision-making tasks involving personal data sharing, where privacy concerns a
arXiv:2606.28615v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains, where free-text explanations such as chain-of-thought and post-hoc rati
arXiv:2606.27644v1 Announce Type: new Abstract: This letter proposes CascadeOcc, a novel occupancy world model that prioritizes intrinsic structural hierarchy over extrinsic auxiliary modalities for a
Conventional model routing sucks. It passes benchmarks but fails to write code you'd actually merge. Introducing Devin Fusion, a new hybrid-model harness for agentic coding. In testing, it reduces the
arXiv:2606.27460v1 Announce Type: new Abstract: In this study, we use a developmental approach to investigate the statistical learning and mental representation of neural language models (NLM). A seri
arXiv:2510.01642v3 Announce Type: replace Abstract: Recent advances in robotic manipulation have integrated low-level robotic control into Vision-Language Models (VLMs), extending them into Vision-Lan
arXiv:2606.27599v1 Announce Type: cross Abstract: While many explainable AI (XAI) methods have been proposed, most are not designed for time-series forecasting models and often rely on the implicit as
arXiv:2606.27617v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) promise fast, parallel language generation, but their reverse transition factorises across token positions -- an approxim
arXiv:2606.27687v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate, classify, and annotate data whose outputs feed downstream hypothesis tests. However, L
arXiv:2603.19466v2 Announce Type: replace Abstract: Effective collaboration begins with knowing when to ask for help. For example, when trying to identify an occluded object, a human would ask someone
arXiv:2606.28105v1 Announce Type: cross Abstract: We develop a quantitative theory of the Random Language Model (RLM), an ensemble of stochastic context-free grammars, in a scaling limit where the num
We recently announced the preview of the BigQuery AI.AGG() function. With AI.AGG(), you can use natural-language instructions within a single line of SQL to summarize or synthesize information over mi