# #benchmarks — MDRSS hashtag feed

> Public MDRSS cards tagged #benchmarks.
> Canonical feed: https://mdrss.com/feeds/benchmarks

## Cards (11)

### [Table of Contents](https://mdrss.com/ai-agents/prompting-and-agent-evaluation/901102/901102.md)

Awesome-LLM-Eval: a curated list of tools, datasets/benchmark, demos, leaderboard, papers, docs and models, mainly for Evaluation on Large Language Models and exploring the boundaries and limits of Generative AI. Use it to build a structured path from fundamentals to hands-on practice.

Classification: ai-agents/prompting-and-agent-evaluation · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [GEO: 300 воспроизводимых GEO-экспериментов — часть 7 из 7 · Backlog из 50 GEO-экспериментов](https://mdrss.com/geo/experiments/900116/900116.md)

Добавить первичную статистику + methodology на 10 страницах и сравнить citation absorption. Comparison table vs narrative-only на matched pages.

Classification: geo/experiments · Feed: geo · Updated: 2026-08-04T12:46:19.671Z · Version: 1

### [GEO: 300 воспроизводимых GEO-экспериментов — часть 6 из 7](https://mdrss.com/geo/experiments/900115/900115.md)

GEO: 300 воспроизводимых GEO-экспериментов — часть 6 из 7 — раздел базы знаний GEO / AI SEO.

Classification: geo/experiments · Feed: geo · Updated: 2026-08-04T12:46:19.623Z · Version: 1

### [GEO: 300 воспроизводимых GEO-экспериментов — часть 5 из 7](https://mdrss.com/geo/experiments/900114/900114.md)

GEO: 300 воспроизводимых GEO-экспериментов — часть 5 из 7 — раздел базы знаний GEO / AI SEO.

Classification: geo/experiments · Feed: geo · Updated: 2026-08-04T12:46:19.570Z · Version: 1

### [GEO: 300 воспроизводимых GEO-экспериментов — часть 4 из 7](https://mdrss.com/geo/experiments/900113/900113.md)

GEO: 300 воспроизводимых GEO-экспериментов — часть 4 из 7 — раздел базы знаний GEO / AI SEO.

Classification: geo/experiments · Feed: geo · Updated: 2026-08-04T12:46:19.521Z · Version: 1

### [GEO: 300 воспроизводимых GEO-экспериментов — часть 3 из 7](https://mdrss.com/geo/experiments/900112/900112.md)

GEO: 300 воспроизводимых GEO-экспериментов — часть 3 из 7 — раздел базы знаний GEO / AI SEO.

Classification: geo/experiments · Feed: geo · Updated: 2026-08-04T12:46:19.472Z · Version: 1

### [GEO: 300 воспроизводимых GEO-экспериментов — часть 2 из 7](https://mdrss.com/geo/experiments/900111/900111.md)

GEO: 300 воспроизводимых GEO-экспериментов — часть 2 из 7 — раздел базы знаний GEO / AI SEO.

Classification: geo/experiments · Feed: geo · Updated: 2026-08-04T12:46:19.420Z · Version: 1

### [GEO: 300 воспроизводимых GEO-экспериментов — часть 1 из 7](https://mdrss.com/geo/experiments/900110/900110.md)

GEO: 300 воспроизводимых GEO-экспериментов — часть 1 из 7 — раздел базы знаний GEO / AI SEO.

Classification: geo/experiments · Feed: geo · Updated: 2026-08-04T12:46:19.371Z · Version: 1

### [medAlpaca: Finetuned Large Language Models for Medical Question Answering](https://mdrss.com/llm-engineering/evaluation/2676/2676.md)

MedAlpaca expands upon both Stanford Alpaca and AlpacaLoRA to offer an advanced suite of large language models specifically fine-tuned for medical question-answering and dialogue applications. Our primary objective is to deliver an array of open-source language models, paving the way for seamless development of medical chatbot solutions.

Classification: llm-engineering/evaluation · Feed: llm-engineering · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Deep Learning for Mathematical Reasoning (DL4MATH)](https://mdrss.com/llm-engineering/evaluation/1284/1284.md)

This repository is the reading list on Deep Learning for Mathematical Reasoning (DL4MATH). Contributors: Pan Lu @UCLA, Liang Qiu @UCLA, Wenhao Yu @Notre Dame, Sean Welleck @UW, Kai-Wei Chang @UCLA For more details, please refer to the paper: A Survey of Deep Learning for Mathematical Reasoning.

Classification: llm-engineering/evaluation · Feed: llm-engineering · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Core ML Stable Diffusion](https://mdrss.com/llm-engineering/serving-and-retrieval/938/938.md)

Run Stable Diffusion on Apple Silicon with Core ML  \ Blog Post\ (https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon)  \ BibTeX\ (#bibtex) This repository comprises: If you run into issues during installation or runtime, please refer to the FAQ section. Please refer to the System Requirements section before getting started.

Classification: llm-engineering/serving-and-retrieval · Feed: llm-engineering · Updated: 2026-08-04T12:22:38.168Z · Version: 1