Moritz Laurer's picture

Moritz Laurer

MoritzLaurer

AI & ML interests

None yet

Recent Activity

updated a Space about 15 hours ago
MoritzLaurer/phoenix-arize-observability-demo
updated a Space about 15 hours ago
MoritzLaurer/hf-model-downloads
published a Space about 16 hours ago
MoritzLaurer/hf-model-downloads
View all activity

Articles

Organizations

Hugging Face's profile picture Amazon SageMaker Community's profile picture  Zero Shot NLI 's profile picture Hugging Test Lab's profile picture Deutsche Gesellschaft fΓΌr internationale Zusammenarbeit's profile picture HuggingFaceM4's profile picture Aledade Inc's profile picture classroom-test-room's profile picture Prezi's profile picture Blog-explorers's profile picture Hugging Face TB Research's profile picture Enterprise Explorers's profile picture ZeroGPU Explorers's profile picture Spectral's profile picture C&A's profile picture Social Post Explorers's profile picture Triple's profile picture Dev Mode Explorers's profile picture moritz-test-organization-changed-2's profile picture Hugging Face Discord Community's profile picture Moritz Test Org's profile picture

Posts 15

view post
Post
1755
Microsoft's rStar-Math paper claims that 🀏 ~7B models can match the math skills of o1 using clever train- and test-time techniques. You can now download their prompt templates from Hugging Face !

πŸ“ The paper introduces rStar-Math, which claims to rival OpenAI o1's math reasoning capabilities by integrating Monte Carlo Tree Search (MCTS) with step-by-step verified reasoning trajectories.
πŸ€– A Process Preference Model (PPM) enables fine-grained evaluation of intermediate steps, improving training data quality.
πŸ§ͺ The system underwent four rounds of self-evolution, progressively refining both the policy and reward models to tackle Olympiad-level math problemsβ€”without GPT-4-based data distillation.
πŸ’Ύ While we wait for the release of code and datasets, you can already download the prompts they used from the HF Hub!

Details and links here πŸ‘‡
Prompt-templates docs: https://moritzlaurer.github.io/prompt_templates/
Templates on the hub: MoritzLaurer/rstar-math-prompts
Prompt-templates collection: MoritzLaurer/prompt-templates-6776aa0b0b8a923957920bb4
Paper: https://arxiv.org/pdf/2501.04519
view post
Post
2913
FACTS is a great paper from @GoogleDeepMind on measuring the factuality of LLM outputs. You can now download their prompt templates from @huggingface to improve LLM-based fact-checking yourself!

πŸ“ The paper introduces the FACTS Grounding benchmark for evaluating the factuality of LLM outputs.

πŸ€– Fact-checking is automated by an ensemble of LLM judges that verify if a response is fully grounded in a factual reference document.

πŸ§ͺ The authors tested different prompt templates on held-out data to ensure their generalization.

πŸ“š It's highly educational to read these templates to learn how frontier labs design prompts and understand their limitations.

πŸ’Ύ You can now download and reuse these prompt templates via the prompt-templates library!

πŸ”„ The library simplifies sharing prompt templates on the HF hub or locally via standardized YAML files. Let’s make LLM work more transparent and reproducible by sharing more templates like this!

Links πŸ‘‡
- prompt-templates docs: https://moritzlaurer.github.io/prompt_templates/
- all templates on the HF Hub: MoritzLaurer/facts-grounding-prompts
- FACTS paper: https://storage.googleapis.com/deepmind-media/FACTS/FACTS_grounding_paper.pdf