Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.
Automated Social Science: Language Models as Scientist and Subjects NBER vs FastDatasets
How do Automated Social Science: Language Models as Scientist and Subjects NBER and FastDatasets compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | Automated Social Science: Language Models as Scientist and Subjects NBER | FastDatasets |
|---|---|---|
| What it is | This NBER paper studies language models as both researchers and subjects in automated social science. | FastDatasets helps create training datasets for large language models. |
| Website | ||
| Type | Website | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Web | Not recorded |
| Open source | Not stated | Yes |
| Language | English | English |
| Alternatives |
Other options to consider
Sites similar to both Automated Social Science: Language Models as Scientist and Subjects NBER and FastDatasets.
SpeechMap.AI compares language models’ refusal rates on controversial speech topics.
LLMeBench provides a flexible framework for benchmarking large language models.
OpenLM Arena compares open language models through leaderboards and benchmark results.
The Hugging Face Open LLM Leaderboard compares language models across evaluation tests including IFEval, MATH, and MMLU-Pro.
An open-source visual programming environment for battle-testing prompts to LLMs.







