datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
llm-misinformation-resistance-index
LLM Misinformation Resistance Index (LMRI)
Formal name: LLM Misinformation Resistance Index (LMRI).
Public alias: the Gaslighting Index — the two headline scores keep their code
names GI-basic and GI-strict, where "GI" comes from the benchmark's public alias.
LMRI measures whether a language model will stand up to its own misinformation.
Each benchmark item is a fabricated conversation in which the assistant's own prior
turn contains a planted false claim (or, for controls, a… See the full description on the dataset page: https://huggingface.co/datasets/buildwithdmytro/llm-misinformation-resistance-index.manipulation-resistant-prompts-1536-1536
Dataset Card: manipulation-resistant-prompts-1536-1536
Dataset Description
This dataset contains prompts with specified target word counts for both input prompts and target outputs, designed to test and evaluate language models across different length requirements. Word counts are defined as whitespace-separated tokens, providing a consistent and human-interpretable measure of text length.
These datasets are typically used in performance benchmarking of language models… See the full description on the dataset page: https://huggingface.co/datasets/metrum-ai/manipulation-resistant-prompts-1536-1536.manipulation-resistant-prompts-1536-96
Dataset Card: manipulation-resistant-prompts-1536-96
Dataset Description
This dataset contains prompts with specified target word counts for both input prompts and target outputs, designed to test and evaluate language models across different length requirements. Word counts are defined as whitespace-separated tokens, providing a consistent and human-interpretable measure of text length.
These datasets are typically used in performance benchmarking of language models… See the full description on the dataset page: https://huggingface.co/datasets/metrum-ai/manipulation-resistant-prompts-1536-96.manipulation-resistant-prompts-96-96
Dataset Card: manipulation-resistant-prompts-96-96
Dataset Description
This dataset contains prompts with specified target word counts for both input prompts and target outputs, designed to test and evaluate language models across different length requirements. Word counts are defined as whitespace-separated tokens, providing a consistent and human-interpretable measure of text length.
These datasets are typically used in performance benchmarking of language models, where… See the full description on the dataset page: https://huggingface.co/datasets/metrum-ai/manipulation-resistant-prompts-96-96.manipulation-resistant-prompts-96-1536
Dataset Card: manipulation-resistant-prompts-96-1536
Dataset Description
This dataset contains prompts with specified target word counts for both input prompts and target outputs, designed to test and evaluate language models across different length requirements. Word counts are defined as whitespace-separated tokens, providing a consistent and human-interpretable measure of text length.
These datasets are typically used in performance benchmarking of language models… See the full description on the dataset page: https://huggingface.co/datasets/metrum-ai/manipulation-resistant-prompts-96-1536.Resilience_Leading_Through_Adversity_Theory
Resilience Leading Through Adversity — Theory
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Resilience_Leading_Through_Adversity_Theory.Resilience_Leading_Through_Adversity_Practical
Resilience Leading Through Adversity — Practical
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Resilience_Leading_Through_Adversity_Practical.