Knowledge catalogue
llama.cpp now supports various small OCR models that can run on low-end devices. These models are small enough to run on GPU with 4GB VRAM, and some of them can even run on CPU with decent performance
arXiv:2604.07343v1 Announce Type: cross Abstract: Pluralistic alignment has emerged as a critical frontier in the development of Large Language Models (LLMs), with reward models (RMs) serving as a cen
The Information: Sources: Nvidia is developing a Nemotron 4 model with 1T+ parameters, up from Nemotron 3 Ultra's 550B parameters but smaller than leading Chinese open models — Nvidia is doubling down
arXiv:2608.07481v1 Announce Type: cross Abstract: This paper investigates whether one large language model can approximate the humor preferences of another in a controlled Cards Against Humanity-style
You probably used @FireworksAI_HQ this week. The cool part is that you just did not know you did. 🎆 Open-source models are free, sure... but the hard part is tailoring them so they perform best on you
I've been out of these forums for awhile but I figured I would provide a formal update on how this has been going now that it has some operation time under its belt, just to put the information out th
arXiv:2607.26173v1 Announce Type: new Abstract: Alignment training, model organisms, and toy models are usually treated as separate research areas. But projects in all three frequently use supervised
arXiv:2607.26448v1 Announce Type: new Abstract: A known limitation of long-context language models is their increasingly unreliable performance in non-additive, set-based aggregation as context length
A Chinese article compiled 52 remarks from Liang Wenfeng’s four-hour investor meeting. I’ve summarised the most important ones below. DeepSeek has one central objective: AGI. This is not the time to m
Frontier AI models have redefined the unit of compute. At trillion-parameter scale, AI training requires thousands of interconnected components, orchestrated in industrial-scale deployments to operate
arXiv:2604.14034v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence, particularly Large Language Models (LLMs), have stimulated growing interest in automating or as
GLM-5.1 by @Zai_org just launched in the Text Arena, and is now the #1 open model. It outperforms the next best open model, its predecessor, GLM-5, by +11 points and +15 over Kimi K2.5 Thinking. It sh
Today the Department of Energy (DOE) and Arcee AI announced the development of Genesis-Science-1 (GS1), an open model for scientific research. This is a joint effort to bring advanced AI into scientif
playing with local AI models and doing some research and came across a fun extrapolation: 'consumer grade graphics cards will be running Fable-equivalent models by 2029' the argument: 1) been said tha
Google Cloud Next ‘26 took place this week in Las Vegas, and the energy was incredible as we welcomed over 32,000 leaders, developers, and partners to explore the Agentic Era with us. Across three key
Introduction Advances in AI model-powered exploitation have demonstrated that general-purpose AI models can excel at vulnerability discovery, even without being purpose-built for the task. Eventually,
Meta announced Muse Spark today, their first model release since Llama 4 almost exactly a year ago. It's hosted, not open weights, and the API is currently 'a private API preview to select users', but
March 6th, 2026 the highest intelligence index score was 51 for frontier models. deepseek-ai/DeepSeek-V4-Flash-0731 that has an intelligence score of 50. If these benchmarks are accurate, models avail
arXiv:2607.20456v1 Announce Type: cross Abstract: Large language models excel at code generation for mainstream programming languages but struggle with rare, domain-specific languages such as MiniZinc
Madison Mills / Axios: Anthropic says Opus 5 is the company's “most aligned model to date”; it is Anthropic's fourth model release in less than two months — Anthropic on Thursday is releasing Claude O
arXiv:2607.21491v1 Announce Type: new Abstract: Do independently trained language models come to represent the same thing in the same way? We answer for code, extending a recently introduced concept-c
arXiv:2607.20988v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models augmented with world modeling represent a promising paradigm for end-to-end autonomous driving. While pixel-level
arXiv:2509.07123v2 Announce Type: replace-cross Abstract: Generalized extreme value models capture dependence among choice alternatives in discrete choice modeling, but require this dependence to be p
arXiv:2407.19633v4 Announce Type: replace Abstract: Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuri
Another new idea to push the state of AI architectures forward. Sakana released a model that effectively uses a mixture of models to get work done. You get a single API but then the work gets farmed o
Big day for American open models... Nemotron 3 Ultra is now the strongest US open-weight model tested, while apparently serving 300+ tok/s 🤯 Comparable large DeepSeek/Kimi models are usually 50-100 to
arXiv:2605.28577v1 Announce Type: new Abstract: AI model hubs provide access to a rapidly growing collection of powerful pre-trained models, enabling off-the-shelf mixture-of-experts systems with diff
arXiv:2507.06803v3 Announce Type: replace-cross Abstract: This paper contributes to speeding up the design and deployment of engineering dynamical systems by proposing a strategy for exploiting domain
arXiv:2604.12955v1 Announce Type: new Abstract: There is growing interest in leveraging large language models (LLMs) for text-to-model translation and optimization tasks. This paper aims to advance th
arXiv:2604.11424v1 Announce Type: new Abstract: Speech Language Models (SLMs) exhibit strong semantic understanding, yet their generated speech often sounds flat and fails to convey expressive intent,
arXiv:2604.10072v1 Announce Type: new Abstract: Recent advancements in the Generative Reward Model (GRM) have demonstrated its potential to enhance the reasoning abilities of LLMs through Chain-of-Tho
arXiv:2607.27506v1 Announce Type: new Abstract: Language and embedding models used in RAG systems are conventionally assumed to require large-scale pretraining and explicit grounding supervision. We p
arXiv:2607.27897v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP, are vulnerable to adversarial attacks, posing a serious problem for real-life applications and deployment.
arXiv:2607.23146v1 Announce Type: new Abstract: Inspired by recent breakthroughs in large language models for natural language processing, foundation models have emerged as a promising paradigm for ze
arXiv:2510.07364v4 Announce Type: replace Abstract: What do thinking language models learn during training that their base models lack? We first present an unsupervised method that discovers a model's
arXiv:2607.03461v1 Announce Type: new Abstract: World models aim to capture environment dynamics in ways that support perception, reasoning, and action, and have recently become a central direction in
arXiv:2606.31048v1 Announce Type: cross Abstract: This paper investigates knowledge distillation from a large reasoning model (DeepSeek-R1) to a compact student model (Qwen2.5-7B). Using historical pr
arXiv:2606.30846v1 Announce Type: new Abstract: Discovering simulation models for reuse remains a fundamental challenge in Modeling and Simulation (M&S). When many models coexist, identifying those th
Run Ornith with Ollama: ollama run ornith For coding, use it with Claude or Pi: ollama launch claude --model ornith ollama launch pi --model ornith For the more capable 35B model, use: ollama launch c
Thanks for running our open-source work on current frontier models “The results are: the most capable models today (GPT-5.5 Pro) did outperform the best models from before (79/100 vs 69/100), but did
arXiv:2606.27288v1 Announce Type: new Abstract: Multi-model LLM systems such as routing, voting, cascades, fusion, and mixture-of-agents are used to beat single-model accuracy. We show that their gain
UBS says 60% of companies now watching AI budgets are moving to cheaper models and open-source Chinese models The pressure is coming from extreme bills, including users spending up to $35K/month, team
arXiv:2606.10905v1 Announce Type: new Abstract: Visual in-Context Learning (VICL) aims at making progress towards adaptive vision models, that can -- based on a few examples -- adapt to a new task at
arXiv:2606.05725v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed through hosted APIs, making model extraction a practical threat to model ownership and service
arXiv:2606.01626v1 Announce Type: new Abstract: Planning with a learned latent world model is a promising route to control from raw pixels, but a strong world model alone is not enough. We show this e
arXiv:2510.02734v2 Announce Type: replace-cross Abstract: Deep learning, particularly with the advancement of Large Language Models, has transformed biomolecular modeling, with protein language models
arXiv:2605.09424v1 Announce Type: new Abstract: Generative modelling is a demanding test of foundation models, because it requires robust, holistic representation learning for a given data modality, r
arXiv:2605.02915v1 Announce Type: new Abstract: Same-model self-verification, prompting a model to audit its own predicted answer, is a plausible confidence signal for selective prediction, but its pr
This Reddit post discusses the viability of using second-hand custom-built RTX 2080 Ti GPUs with 22GB VRAM for running Stable Diffusion models in ComfyUI, including whether two cards could be linked v
Introducing talkie: a 13B vintage language model from 1930 New project from Nick Levine, David Duvenaud, and Alec Radford (of GPT, GPT-2, Whisper fame). talkie-1930-13b-base (53.1 GB) is a '13B langua
arXiv:2506.07298v3 Announce Type: replace-cross Abstract: Hidden Markov Models (HMMs) are foundational tools for modeling sequential data with latent Markovian structure, yet fitting them to real-worl
Qwen3.6 and gemma 4 just shown that we were still far from capability limit on small models, we still are. Huge models are good, but is there really a point in going bigger. Just realize something. On
arXiv:2608.06723v1 Announce Type: cross Abstract: The rapid scaling of Large Language Models (LLMs) has significantly increased computational cost, energy consumption, and inference latency, making ac
After evaluating one of our upcoming models, Astra, we're treating it as our first 'critical' model for cybersecurity under our Preparedness Framework. This is a scenario we've planned for, and we're
DeepSeek-V4-Flash-0731 is Ollama's fastest growing model ever in token usage. We are scaling capacity in US & Europe. On Ollama, this model runs with high performance (100tps+) and zero data retention
Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on re
dam bois we eating good this week ngl, The velocity of the open_weight ecosystem right now is hitting a point where proprietary, closed-source APIs are losing their leverage on compute intelligence. W
🚀langchain launches this week: all about open source models and memory! First: open source models. We partnered with @NVIDIAAI to launch a NemoClaw DeepAgents blueprint. This pairs Deep Agents (our op
arXiv:2506.01260v2 Announce Type: replace Abstract: Scaling models has led to significant advancements in deep learning, but training these models in decentralized settings remains challenging due to
Video models are hard. Real-time video models are even harder. Loved this breakdown by @itunpredictable on how we productionized Runway Characters, our real-time interactive avatar model. We had to fi