Search: “models”

the deeper point: model choice and harness choice aren't independent variables. benchmarking a model without specifying the harness is like benchmarking a chip without specifying the compiler. the num

arXiv:2605.00994v1 Announce Type: new Abstract: Finetuning can significantly modify the behavior of large language models, including introducing harmful or unsafe behaviors. To study these risks, rese

arXiv:2605.02684v1 Announce Type: new Abstract: Spectral-based machine learning models have been increasingly deployed in chemometrics and spectroscopy, where predictive accuracy is as important as ex

open weight models are having a moment @masondrxy is making deepagents cli a coding harness that works amazing with open weight models what is missing? what should he add? try it out! deepagents-cli i

The year of the harness 🤝 Harnesses are our most direct layer to turn a model into a great product experience for users by shaping model behavior towards a goal This matters today because models have

arXiv:2604.22018v1 Announce Type: cross Abstract: Several brain foundation models (FM) have recently been proposed to predict brain disorders by modelling dynamic functional connectivity (FC). While t

Spot on 🎯 We don't need frontier intelligence to automate searches and sending emails - We don't need trillion parameter models to be able to summarize articles or technical documents - We don't need

arXiv:2503.17239v3 Announce Type: replace-cross Abstract: Fine-tuning large language models (LLMs) is a common practice to adapt generalist models to specialized domains. However, recent studies show

arXiv:2510.18457v3 Announce Type: replace Abstract: The performance of Latent Diffusion Models (LDMs) is critically dependent on the quality of their visual tokenizers. While recent works have explore

Vincent Chow / South China Morning Post: Tencent releases Hy3-preview, its first AI model developed under former OpenAI researcher Yao Shunyu; the model features 295B parameters, down from HY2's 400B

arXiv:2510.26782v3 Announce Type: replace-cross Abstract: A world model is an internal model that simulates how the world evolves. Given past observations and actions, it predicts the future physical

arXiv:2510.07248v3 Announce Type: replace Abstract: Small language models (SLMs) enable scalable tool-augmented multi-agent systems where multiple SLMs handle subtasks orchestrated by a powerful coord

I tested @huggingface ml-intern, given the prompt 'Fine-tune a Segment Anything Model (SAM) on a useful medical dataset. Train the model, and provide a comprehensive tutorial in a Jupyter Notebook fil

arXiv:2604.07484v1 Announce Type: cross Abstract: Generative reward models (GRMs) have emerged as a promising approach for aligning Large Language Models (LLMs) with human preferences by offering grea

arXiv:2604.06483v1 Announce Type: cross Abstract: Large language models that require multiple GPU cards to host are usually the most capable models. It is necessary to understand and steer these model

arXiv:2503.13551v5 Announce Type: replace Abstract: Recent studies show that Large Language Models (LLMs) achieve strong reasoning capabilities through supervised fine-tuning or reinforcement learning

Anthropic investigated the internal mechanisms of its latest unreleased model, Claude Mythos Preview, and what they found is 100% worth a read. Key things I pulled from Anthropic researchers' threads:

.@steipete has been an amazing supporter of open models and local models. This is even before the rise of OpenClaw. 🦞 Ollama is here to love. ❤️ Let's make the world a better place together. Some folk

arXiv:2608.10107v1 Announce Type: new Abstract: Emerging World-Action Models (WAMs) have demonstrated promising performance in autonomous driving by jointly modeling future driving scene evolution and

arXiv:2608.10837v1 Announce Type: cross Abstract: The strong performance of foundation models for tabular tasks comes at substantial inference costs. Distilling models into task-specific architectures

NVIDIA Nemotron 3.5 Lighting is available on Ollama! It's a 30B model made for always-on agents. All local. Claude Code ollama launch claude --model nemotron-3.5-lightning Hermes Agent ollama launch h

A few months ago, I had the idea of making a LLM from scratch as a personal project (for learning and partly for improving my resume). Since I learned a lot from other posts on here over the past year

LFM2.5-2.6B is a new tiny model by LiquidAI, with benchmarks that put it head to head with much larger models. I've run llama-perplexity on many model GGUF quants, crossed with many KV cache quants, t

For a very long time most high-performing AI models were end-to-end neural models; vector input -> vector output, with only ultra-thin symbolic preprocessing and postprocessing layers (e.g. label deco

New York Times: Developers in Africa are increasingly choosing Chinese open-source AI models over US models, saying they are downloadable, easier to customize, and much cheaper — Developers built Sunf

arXiv:2607.27797v1 Announce Type: new Abstract: Predictive process monitoring (PPM) leverages event logs to forecast the future of running process instances, for instance, predicting the next activity

I was surprised to see that Deepseek V4 Flash is extremely smart and small enough to fit in setup that can be built with < $50,000. Expensive, but not a datacenter. So I wanted to see the trend over t

Introducing the Parse Gateway There's been an explosion of interest in model routing - you don't always need the best model for every task. That is especially true for document parsing 📄🔀: - Some page

arXiv:2607.23976v1 Announce Type: cross Abstract: Appending a two-word confirmation tag to a decision question -- 'Is X the better choice?' versus 'X is the better choice, right?' -- changes whether a

arXiv:2607.22535v1 Announce Type: cross Abstract: Action-conditioned video world models predict future observations from an initial observation and an action signal. In robotics, actions influence fut

arXiv:2607.22034v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly deployed on consumer hardware where input images are degraded by compression, camera shake, and poor li

There is a lot of buzz around running 100B parameter models on cheap local hardware using ternary (1.58-bit) quantization like Microsoft's BitNet architecture. The theoretical hardware shortcuts are i

Yes, open-source / open-weight models are important for a healthy AI ecosystem. That's how we can verify things, check claims, and keep up outside the closed labs. Plus, it gives us the freedom to run

Model quantization has become essential for efficient large language model deployment, yet existing approaches involve clear trade-offs: methods such as GPTQ and AWQ achieve practical compression but

Interesting finding on frontier models. It turns out that frontier models can write proofs but stumble on faithfully copying a long block of text. This has huge implications. It sounds trivial, which

I think OpenRouter is not a good measure of actual model usage in a world of agentic tools (not that I doubt that Chinese open weights model usage is up, but this could also look like a graph of usage

arXiv:2607.07729v1 Announce Type: cross Abstract: As foundation models grow in scale and diversity, coordinating multiple models into cooperative reasoning systems offers a path toward safer, more rel

Cursor announced that Grok 4.5 and Composer represent distinct model weight classes, with Composer 2.5 continuing to be available while new models in that size category will be released. This indicate

arXiv:2607.02642v1 Announce Type: new Abstract: Evaluating embodied robot foundation models remains a critical bottleneck; unlike large language models efficiently assessed via digital benchmarks, rob

arXiv:2607.04360v1 Announce Type: cross Abstract: Conditional generative models have emerged as powerful tools for sampling from target conditional distributions, driving substantial advances across a

arXiv:2607.03347v1 Announce Type: new Abstract: We consider the Multiscale Single-Index Model (MSIM), first introduced in ite{oymak2021learning}, as a stylized model for hierarchical learning with sca

Databricks introduces Vibe Data Modeling, a new approach to data modeling designed specifically for lakehouse architectures that aims to simplify and improve how organizations structure and manage dat

Dean Takahashi / GamesBeat: Tripo AI, which is developing 3D foundation models and world models for use in games, raised 150M, a month after it said it raised 200M — Tripo AI, a global artificial inte

Alex Stamos / @alexstamos: [Thread] The US' now-lifted export controls on Anthropic models created uncertainty, are an own goal, and will push service providers towards Chinese AI models — A lot to un

Watch Devin Fusion work: The sidekick model handles fetching information and skimming sources. The frontier model makes a plan for implementation, then delegates well-scoped sub-tasks to the sidekick

arXiv:2601.07965v2 Announce Type: replace Abstract: When a model knows when it does not know, many possibilities emerge. The first question is how to enable a model to recognize that it does not know.