Search: “models”

arXiv:2606.31551v1 Announce Type: new Abstract: Training language models (LMs) remains a highly human-intensive process, even as frontier language model agents become increasingly capable at software

NEW on Hugging Face: Hardware filters 🖥️ A new Hardware filter on the Models page results to models that fit a specific GPU, CPU, or Apple Silicon chip, so you only see what will actually run on your

arXiv:2606.25086v1 Announce Type: new Abstract: Many modern Language Model (LM) pipelines return an averaged model, such as an exponential moving average of the training iterates, rather than the fina

arXiv:2606.24650v1 Announce Type: new Abstract: We present Harmonic, a hierarchical state space model (SSM) for language modeling. The architecture stacks three recurrent levels at progressively slowe

We benchmarked Mistral OCR against other frontier and open-weight models on ParseBench 📊 For a model at its price point, it is quite competitive! - It wins on semantic formatting - understanding strik

GLM is the kind of model that revives serious interest in open source AI. It passes the blind test relative to the frontier models on the median production grade knowledge worker task. It’s affordable

arXiv:2606.12072v1 Announce Type: new Abstract: Pretrained video generators are promising visual world models that exhibit emergent task-solving abilities; however, their reliance on detailed textual

arXiv:2606.10620v1 Announce Type: cross Abstract: Image generation models now produce high-quality static images, yet their ability to represent how a visual world changes over time remains poorly und

The Keyword: Google introduces DiffusionGemma, an experimental 26B-parameter open model that uses text diffusion for faster text generation compared to autoregressive models — Our newest open experime

arXiv:2601.23231v2 Announce Type: replace-cross Abstract: Flow-based generative models provide strong unconditional priors for inverse problems, but guiding their dynamics for conditional generation r

The post highlights strong market demand for efficient small language models under 9 billion parameters, citing Qwen's top-downloaded models as evidence of user preference for compact, resource-effici

Two bits here I think we're going to see a lot more: 1. custom harnesses / finetunes on smaller open source models to beat frontier models at specific skill or task 2. using frontier models as critics

arXiv:2605.29585v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to answer questions about physical scenes, yet most evaluations reduce performance to a final answer

arXiv:2605.28769v1 Announce Type: new Abstract: Softmax attention is the cornerstone of modern large language models, but its memory scales linearly and compute quadratically with sequence length. Lin

arXiv:2512.15605v4 Announce Type: replace Abstract: Autoregressive models (ARMs) currently constitute the dominant paradigm for large language models (LLMs). Energy-based models (EBMs) represent anoth

Closed and gated surveillance economy SaaS systems and models will get replaced by open source in two tiers: - The models themselves - The everything-ultra-app harness If an American open source champ

arXiv:2605.22356v1 Announce Type: new Abstract: Large language models are increasingly used as computational tools for modeling human-like behavior. We introduce a behavioral induction framework that

arXiv:2602.16813v3 Announce Type: replace Abstract: Language models based on discrete diffusion have attracted widespread interest for their potential to provide faster generation than autoregressive

arXiv:2602.18895v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promise in translating model-based explanations into human-readable narratives. This study evaluates w

arXiv:2605.16713v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) achieve strong semantic recognition, yet remain brittle on elementary spatial relations such as left of, on, behi

arXiv:2601.23068v2 Announce Type: replace-cross Abstract: Computing the importance of features in supervised classification tasks is critical for model interpretability. Shapley values are a widely us

A new set of open-weight models is topping the leaderboard for document understanding 🔥 INF just released two models: Infinity-Parser2-Pro (35B) and Infinity-Parser2-Flash (2B) that top our @huggingfa

arXiv:2605.11165v1 Announce Type: new Abstract: Federated learning (FL) in heterogeneous environments remains challenging because client models often differ in both architecture and data distribution.

AI Security Institute: Mythos Preview is the first AI model to complete both of AISI's cyber ranges, which measure models' cyberattack capabilities; GPT-5.5 solved only one of them — In February 2026,

arXiv:2605.11167v1 Announce Type: new Abstract: Existing multi-model and tool-augmented systems communicate by generating text, serializing every exchange through the output vocabulary. Can two pretra

arXiv:2603.14186v4 Announce Type: replace Abstract: State-of-the-art text-to-image models produce high-quality images, but inference remains expensive as generation requires several sequential ODE or

Multi-Token Prediction (MTP) for LLaMA.cpp! Running Gemma4 local model 1.5x faster. We patched LLaMA.cpp. Quantized Gemma 4 assistant models into GGUF format. We ran tests on a MacBook Pro M5Max. Gemm

arXiv:2508.15202v2 Announce Type: replace Abstract: Process Reward Models (PRMs) supervise intermediate reasoning steps in large language models (LLMs), but existing PRMs are mainly trained on general

arXiv:2512.05525v2 Announce Type: replace-cross Abstract: Businesses increasingly rely on large language models (LLMs) to automate simple repetitive tasks instead of developing custom machine learning

NIST: An evaluation by NIST's CAISI says DeepSeek V4 Pro lags behind leading US AI models by about eight months and is the most capable Chinese AI model to date — In April 2026, the Center for AI Stan

What people call 'distillation' is a super common practice (you use other models to benchmark your model, to evaluate your inputs or to add a little bit to your datasets) that in my opinion should be

Evelyn Cheng / CNBC: Alibaba says its Qwen AI models will be integrated into BYD, Volkswagen, and other cars, letting users buy food and tickets via voice commands on select models — BEIJING — Chinese

🚨BREAKING: Hugging Face just open-sourced an AI intern that reads ML papers, trains models, and ships the final model for you. It’s called ML Intern. And this is not another AI coding demo that prints

Bloomberg: DeepSeek releases its new flagship models V4 Pro and V4 Flash in preview, saying V4 Pro trails the performance of state-of-the-art models by about 3 to 6 months — DeepSeek rolled out previe

arXiv:2604.01965v2 Announce Type: replace-cross Abstract: Scientific knowledge discovery increasingly relies on large language models, yet many existing scholarly assistants depend on proprietary syst

arXiv:2604.19598v1 Announce Type: cross Abstract: This study compared repeated generation consistency of exercise prescription outputs across three large language models (LLMs), specifically GPT-4.1,

APIs and limited releases for AI models are not a safety policy, they’re a business model (which is totally ok as long as you’re transparent about it). Especially on cyber-security, they give a false

It’s time to go beyond language models. Introducing Odyssey-2 Max, our most powerful world model yet. It materially advances the SOTA in physical accuracy. This is a big step toward models that simula

arXiv:2509.13047v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across many domains, yet their application to specialized fields remain

great read on why open harnesses have become so important. we used to focus on open models vs closed models, but i think the deeper issue is open harnesses vs closed harnesses. if the harness is close

Quartermaster (my local inference manager: one server that swaps llama.cpp, image, audio and video models in and out of VRAM) can now help you server and manage decision models: Auto-discovered. Drop

arXiv:2603.16148v2 Announce Type: replace Abstract: Spiking neural networks promise brain-inspired neural dynamics, yet native large-scale spiking language-model pretraining remains largely unexplored

arXiv:2607.16204v2 Announce Type: replace Abstract: Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixe

Preamble and disclaimer, Sample size: 8, at any size of form this research is just screwing around being writing it down. This was just a little,(well... big), curiosity test I wanted to run to see wh

arXiv:2510.19773v2 Announce Type: replace Abstract: Membership inference attacks (MIAs) have emerged as the standard tool for evaluating the privacy risks of AI models. However, state-of-the-art attac

arXiv:2610.09134v1 Announce Type: new Abstract: Robot world models support policy evaluation, planning, and synthetic data generation, but these applications require predictions that distinguish succe