Knowledge catalogue
Today, Gemini 3.1 Flash TTS, our latest text-to-speech model, is available on Google AI Studio and Vertex AI. It delivers precise controllability and expressivity, empowering developers and enterprise
arXiv:2604.12397v1 Announce Type: new Abstract: Standard Large Language Model (LLM) pre-training typically treats corpora as flattened token sequences, often overlooking the real-world context that hu
arXiv:2604.12596v1 Announce Type: cross Abstract: We introduce KumoRFM-2, the next iteration of a pre-trained foundation model for relational data. KumoRFM-2 supports in-context learning as well as fi
arXiv:2502.17403v5 Announce Type: replace-cross Abstract: Electronic Health Records (EHRs) offer considerable potential for clinical prediction, but their complexity and heterogeneity challenge tradit
arXiv:2507.22359v4 Announce Type: replace Abstract: Although large language models (LLMs) have shown exceptional capabilities across a wide range of tasks, reliable evaluation remains a critical chall
The Tesla Model 3 Performance is showcased in a spring-themed promotional post shared via the Tesla Asia X account, featuring cherry blossom imagery that suggests an Asian market campaign. The post hi
A mid-2026 outlook piece from the Interconnects AI newsletter in which the author makes specific predictions about the trajectory of open-weight language models, likely covering expected capability mi
arXiv:2604.12668v1 Announce Type: new Abstract: The Diffusion Probabilistic Model (DPM) achieves remarkable performance in image generation, while its increasing parameter size and computational overh
arXiv:2604.12446v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models have achieved remarkable success in image synthesis, but their reliance on large-scale data and open ecosystems i
arXiv:2410.01473v2 Announce Type: replace Abstract: Soil sinkholes significantly influence soil degradation, infrastructure vulnerability, and landscape evolution. However, their irregular shapes, com
Small models are cheap to run, but expensive to adapt. The hard part is not only fine-tuning. It is the surrounding loop that involves collecting data, diagnosing failures, building evals, avoiding re
arXiv:2604.12617v1 Announce Type: cross Abstract: The post-training pipeline for diffusion models currently has two stages: supervised fine-tuning (SFT) on curated data and reinforcement learning (RL)
arXiv:2603.18846v2 Announce Type: replace Abstract: Foundation models are used to extract transferable representations from large amounts of unlabeled data, typically via self-supervised learning (SSL
The Ollama Cloud Subscription includes a feature described as 'Run cloud models at a time,' which refers to how many AI models a user can have simultaneously loaded and running in the cloud at any giv
arXiv:2604.11332v1 Announce Type: cross Abstract: Deep learning has markedly advanced image based plant disease diagnosis as improved hardware and dataset quality have enabled increasingly accurate ne
Anthropic: Anthropic details using AI agents to accelerate alignment research on “weak-to-strong supervision”, where a weak model supervises the training of a stronger one — Large language models' eve
arXiv:2604.11490v1 Announce Type: new Abstract: While the field of vision-language (VL) has achieved remarkable success in integrating visual and textual information across multiple languages and doma
arXiv:2604.10874v1 Announce Type: cross Abstract: Adverse Outcome Pathways (AOPs) are an important knowledge framework in toxicological research and risk assessment. In recent years, large language mo
arXiv:2504.14988v3 Announce Type: replace Abstract: Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated remarkable multimodal perception capabilities, garnering significant a
arXiv:2604.10597v1 Announce Type: cross Abstract: State Space Models (SSMs), represented by the Mamba family, provide linear-time sequence modeling and are attractive for long-context inference. Yet p
arXiv:2604.10514v1 Announce Type: cross Abstract: Surgical phase segmentation is central to computer-assisted surgery, yet robust models remain difficult to develop when labeled surgical videos are sc
arXiv:2604.10014v1 Announce Type: cross Abstract: This paper provides a comprehensive evaluation of demographic and linguistic biases in omnimodal language models that process text, images, audio, and
arXiv:2604.10567v1 Announce Type: cross Abstract: Diffusion-based language models (dLLMs) have emerged as a promising alternative to autoregressive language models, offering the potential for parallel
arXiv:2604.11576v1 Announce Type: new Abstract: Despite their impressive zero-shot abilities, vision-language models such as CLIP have been shown to be susceptible to adversarial attacks. To enhance i
Harrison Chase's post explores the divergent strategic incentives around memory in AI agent systems, arguing that for those building agent frameworks, persistent memory creates compounding value and c
arXiv:2512.18073v2 Announce Type: replace Abstract: Multimodal LLMs (MLLMs) are capable of performing complex data analysis, visual question answering, generation, and reasoning tasks. However, their
arXiv:2604.11041v1 Announce Type: new Abstract: Semiconductor supply chains face unprecedented resilience challenges amidst global geopolitical turbulence. Conventional Large Language Model (LLM) plan
arXiv:2604.10591v1 Announce Type: cross Abstract: Effective foundation modeling in remote sensing requires spatially aligned heterogeneous modalities coupled with semantically grounded supervision, ye
arXiv:2604.11348v1 Announce Type: new Abstract: Efficient and explainable breast cancer (BC) risk prediction is critical for large-scale population-based screening. Breast MRI provides functional info
arXiv:2604.11216v1 Announce Type: new Abstract: What values, evidence preferences, and source trust hierarchies do AI systems actually exhibit when facing structured dilemmas? We present the first lar
arXiv:2602.21950v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have shown great potential in medical applications, yet existing benchmarks inadequately capture real-world
arXiv:2604.11502v1 Announce Type: cross Abstract: Contextual causal reasoning is a critical yet challenging capability for Large Language Models (LLMs). Existing benchmarks, however, often evaluate th
arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio
NEW: Added @OpenRouter's new free stealth model, Elephant-Alpha, to Hermes Agent, which you can now access if you run `hermes update`! I also had Hermes come up with an agentic benchmark on the fly to
Technology and computing giant Nvidia Corp. today announced the release of Ising, the world’s first open artificial intelligence model family aimed at quantum computing calibration and error correctio
arXiv:2604.10866v1 Announce Type: new Abstract: AI agents are expected to perform professional work across hundreds of occupational domains (from emergency department triage to nuclear reactor safety
OpenAI Group PBC today announced the launch of GPT-5.4-Cyber, a fine-tuned variant of its GPT-5.4 model designed for defensive cybersecurity work and also announced a significant expansion of its Trus
arXiv:2602.13847v3 Announce Type: replace-cross Abstract: We present a framework for constructing physics and causally constrained neural models of turbulent dynamical systems from data. We first form
arXiv:2604.10171v1 Announce Type: new Abstract: This manuscript presents PoreDiT, a novel generative model designed for high-efficiency digital rock reconstruction at gigavoxel scales. Addressing the
arXiv:2603.16068v3 Announce Type: replace-cross Abstract: Given limited and costly computational infrastructure, resource efficiency is a key requirement for large language models (LLMs). Efficient LL
arXiv:2604.10465v1 Announce Type: cross Abstract: Diffusion models are often introduced from multiple perspectives, such as VAEs, score matching, or flow matching, accompanied by dense and technically
arXiv:2510.17516v4 Announce Type: replace-cross Abstract: Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only i
The future is open. At GTC Live, @cohere Co-founder & CEO, Aidan Gomez describes how open models give developers the autonomy they need to scale 📈, customize and innovate their way into the future of
Today we're releasing SWE-check, a specialized bug detection model we RL-trained with @appliedcompute that matches frontier performance on internal in-distribution evals and makes meaningful progress
arXiv:2604.10733v1 Announce Type: cross Abstract: Large language models increasingly serve as conversational agents that adopt personas and role-play characters at user request. This capability, while
arXiv:2604.10999v1 Announce Type: new Abstract: Vision-language models (VLMs) perform strongly on many multimodal benchmarks. However, the ability to follow complex visual paths -- a task that human o
arXiv:2604.10055v1 Announce Type: new Abstract: Despite their strong performance in embodied tasks, recent Vision-Language-Action (VLA) models remain highly fragile under multimodal perturbations, whe
This Reddit post from r/MachineLearning discusses the concept of decomposing machine learning models into a graph database representation, treating a model's components — such as layers, weights, and
arXiv:2604.10827v1 Announce Type: new Abstract: Compute scaling for LLM reasoning requires allocating budget between exploring solution approaches (breadth) and refining promising solutions (depth). M
arXiv:2604.09364v1 Announce Type: cross Abstract: When a Vision-Language Model (VLM) sees a blue banana and answers 'yellow', is the problem of perception or arbitration? We explore the question in te
arXiv:2604.09029v1 Announce Type: cross Abstract: Large language models have been widely explored as decision-support tools in high-stakes domains due to their contextual understanding and reasoning c
arXiv:2604.08591v1 Announce Type: cross Abstract: Hallucinations in large ASR models present a critical safety risk. In this work, we propose the extit{Spectral Sensitivity Theorem}, which predicts a
arXiv:2604.09459v1 Announce Type: new Abstract: Reinforcement learning (RL) for large language models (LLMs) increasingly relies on sparse, outcome-level rewards -- yet determining which actions withi
This r/ollama thread discusses community advice on configuring a locally-run AI model (via Ollama) to automatically generate Word documents or reports, covering topics such as model selection, scripti
arXiv:2604.08559v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-wor
arXiv:2604.02319v2 Announce Type: replace Abstract: When posed with prompts that permit a large number of valid answers, comprehensively generating them is the first step towards satisfying a wide ran
arXiv:2511.19704v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) underpins many vision and robotics tasks that require generalizable semantic understanding. Existing ap
arXiv:2512.04072v2 Announce Type: replace-cross Abstract: Reasoning models leveraging long chains of thought employ various cognitive skills, such as verification of their answers, backtracking, retry
arXiv:2604.08815v1 Announce Type: new Abstract: Medical vision-language models (VLMs) show strong performance on radiology tasks but often produce fluent yet weakly grounded conclusions due to over-re
In March 2026 there were 70,663 EV's registered in Germany, Tesla had almost 10% of that market. And Model Y was the best-selling EV in the country. I suspect those 10% will be kinder garden numbers c