Search: “models”

🚨 A year ago, OpenMed didn't exist. Today: 340M model downloads. 1,500+ open medical models, all Apache 2.0. 650+ run on your iPhone, fully on-device. Started by one person. Now built by a community.

Open models are not just a pricing story. They are what happens when the AI stack becomes modular: models, APIs, harnesses, tools, and inference all improving independently. Together AI is building th

Tomorrow, we're releasing an ML model for on-device PII redaction, which is far smaller than existing models, but is surprisingly effective. It is a first iteration. Will be live at 12:30! A big relea

Wall Street Journal: Researchers say Z.ai's GLM-5.2 matches latest US models at finding security bugs, as critics question the US' lax approach in restricting Chinese open models — Clampdown on top U.

arXiv:2606.26981v1 Announce Type: cross Abstract: Synthesizing human motion from textual descriptions is essential for immersive digital applications, yet existing methods face a persistent trade-off

Not sure if that's a change in default preferences from the models or just that I'm often prompting inside existing projects and the models know full well not to introduce React to a project that isn'

Kenneth Shepard / Kotaku: Microsoft says the price of Xbox consoles will increase on August 1 by 100 for 512GB models and 150 for 1TB models, the third price increase since 2025 — Microsoft is increas

Open + closed models = better together. Our previous research with @harvey showed the benefits of combining a frontier closed model as an advisor agent with fine-tuned, open-source worker agents. Thre

We're sharing new research on how models hack public benchmarks. The latest models, including Opus 4.8 and Composer 2.5, learn to retrieve solutions from the internet or git history. When we apply a s

arXiv:2606.24162v1 Announce Type: new Abstract: Foundation models have been increasingly applied to behavioral science domains such as psychology, sociology, and economics. While these models show pro

arXiv:2606.24742v1 Announce Type: new Abstract: Generalist value models play a pivotal role in scaling robotic policy learning from large-scale, mixed-quality data. Mathematically, accurate value esti

arXiv:2606.23574v1 Announce Type: cross Abstract: Vision-language-action (VLA) models and world-action models (WAM) are the generative models now driving general-purpose robot control, turning raw cam

arXiv:2606.21173v1 Announce Type: new Abstract: Model-based and model-free reinforcement learning are traditionally viewed as separate paradigms: instead of learning a model of the transition kernel P

arXiv:2606.09643v1 Announce Type: cross Abstract: Foundation models (FMs) are increasingly used as backbones for downstream tasks across language, vision, time-series, and multimodal applications. Yet

Krea 2 is @krea_ai's first foundation model built from scratch. Most models render what you describe. Krea 2 interprets the mood, style, and direction behind it. Simple prompts → wide range of distinc

We trained language models that compress massive contexts into tiny latent representations. Latent Context Language Models (LCLMs) outperform existing KV cache compression methods on the latency/accur

arXiv:2602.17907v2 Announce Type: replace-cross Abstract: Traditional neural topic models are typically optimized by reconstructing the document's Bag-of-Words (BoW) representations, overlooking conte

arXiv:2606.04739v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generatio

arXiv:2606.05004v1 Announce Type: cross Abstract: With the widespread deployment of public large language models (LLMs) such as ChatGPT, protecting user prompt privacy has become an increasingly criti

arXiv:2601.22841v2 Announce Type: replace Abstract: Large-scale foundation models (FMs) in remote sensing (RS) (denoted as RS FMs) are developed following paradigms established in computer vision (CV)

This Reddit discussion from r/ollama explores user experiences with uncensored Ollama language models, featuring anecdotal accounts of unusual or extreme use cases and recommendations for popular unce

Reed Albergotti / Semafor: An interview with Microsoft AI CEO Mustafa Suleyman about its models catching up to the state of the art from months ago, refusing to distill models, and more — THE SCENE —

arXiv:2603.10619v2 Announce Type: replace Abstract: The recent success of large pre-trained language models (PLMs) has motivated their integration into topic modeling. However, PLM-augmented topic mod

arXiv:2601.03309v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models, which integrate pretrained large Vision-Language Models (VLM) into their policy backbone, are gaining sig

arXiv:2605.30642v1 Announce Type: new Abstract: Generative models have a persistent limitation: their tendency to memorize training data can create legal liabilities and erode creative diversity. Unde

I've been using state-of-the-art models to teach small models running on my computer how I work. The result : a personal agent that runs my inbox, my deal pipeline, my blog, my calendar, & my research

arXiv:2605.29360v1 Announce Type: new Abstract: Action-conditioned world models are increasingly used as scalable simulators for robot learning, yet current evaluations provide limited evidence that t

arXiv:2510.22437v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) solve complex tasks by generating long Chain-of-Thought (CoT) sequences; however, the emergent dynamics governing reas

Most people know Hugging Face from its public models and datasets but few realize that 50% of the models and datasets stored on HF are private. This number has been increasing with buckets (our S3 alt

arXiv:2605.28563v1 Announce Type: cross Abstract: Evaluating foundation models under appropriate adaptation settings is essential for understanding the quality and transferability of the learned repre

arXiv:2407.21075v2 Announce Type: replace Abstract: We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficie

Narrative violation: Open model use in Factory has more than 3x’d in the last month relative to closed models. By both total consumption and event count. Will be interesting to see what open vs closed

arXiv:2605.27589v1 Announce Type: new Abstract: Video generation models are increasingly used as world simulators for tasks like driving and robotic manipulation. What matters in these settings is not

arXiv:2605.24642v1 Announce Type: cross Abstract: Recent work explores new opportunities at the intersection of vision-language-action models (VLAs) and geometric foundation models (GFMs) for 3D recon

arXiv:2605.23754v1 Announce Type: new Abstract: Developing constitutive models that capture how materials deform under load traditionally requires years of specialized expertise in continuum mechanics

arXiv:2605.20337v1 Announce Type: new Abstract: How interpretable are the features of leading vision models? The question is increasingly pressing as these models move from research benchmarks into hi

arXiv:2605.19726v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) enable globally coherent, bidirectional, and controllable text generation, offering advantages over traditional autoreg

We ran 720 browser agent tasks with @nottecore across frontier models. One baseline model produced malformed outputs in ~1 out of every 5 calls, leading to retries inside multi-step workflows. Across

arXiv:2604.01674v2 Announce Type: replace Abstract: Model merging aims to integrate multiple expert models into a single model that inherits their complementary strengths without incurring the inferen

arXiv:2602.01970v2 Announce Type: replace Abstract: Reinforcement learning enhances the reasoning capabilities of large language models but often involves high computational costs due to rollout-inten

arXiv:2605.13030v1 Announce Type: cross Abstract: Model merging combines task experts into one model and avoids joint training, retraining, or deploying many expert models, but the merged model often

arXiv:2605.13587v1 Announce Type: cross Abstract: Near-infrared spectroscopy (NIRS) is rapid and non-destructive, but reliable calibration still depends heavily on spectral preprocessing. In routine p

Yann LeCun says you cannot build a reliable agentic system without a world model LLMs don't have world models. They can't predict the consequences of their actions before taking them 'they just act, a

arXiv:2605.10419v1 Announce Type: cross Abstract: This paper investigates the effectiveness of large language models (LLMs) in answering questions over datasets. We examine their performance in two sc

arXiv:2602.04093v2 Announce Type: replace Abstract: Concept-based Models (CMs) enhance interpretability in deep learning by grounding predictions in human-understandable concepts. However, concept ann

Introducing Flux Matching, a generative modeling paradigm that generalizes diffusion models to vector fields that need not be the score function. Enables structural priors in the dynamics, faster samp