datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
recursive-latent-reasoning
Recursive Latent Reasoning — datasets
Data for the Recursive Latent Reasoning project: one shared recursive generator
(a TRM-style weight-tied block refining a VAE latent canvas, with a frozen multi-scale
MAE as the feature ruler) applied to three tasks.
domain
unit
input → target
objective
crystal/
a SLICES row
target band_gap → a valid crystal
MAE-based generation, 2 arms: plain vs GFN multi-reward
sudoku/
a (puzzle, solution) pair
puzzle → its unique solution… See the full description on the dataset page: https://huggingface.co/datasets/iamseungpil/recursive-latent-reasoning.Vinayak-Multistep-Recursive-Reasoning-Benchmark
Vinayak Multistep Recursive Reasoning Benchmark (VMRRB)
Overview
The Vinayak Multistep Recursive Reasoning Benchmark (VMRRB) is a large-scale prompt-based benchmark designed to evaluate advanced reasoning, recursive dependency resolution, encrypted task traversal, and robustness capabilities of frontier AI systems.
The benchmark evaluates a model's ability to:
Perform recursive multistep reasoning
Resolve interdependent question chains
Execute encrypted dependency… See the full description on the dataset page: https://huggingface.co/datasets/bepipeV/Vinayak-Multistep-Recursive-Reasoning-Benchmark.samantha-r01-recursive-reasoning-corpus
Samantha R01 Recursive Reasoning Corpus
Answer-only corpus for the first isolated Samantha silent-tick / recursive-latent-reasoning validation. It is normalized for pre_train_recursive_reasoning.py and intentionally contains no visible chain-of-thought or source rationale fields.
The repository is private because it combines sources with mixed or unspecified redistribution terms. Access does not supersede any upstream license.
Split policy
train: 50,000… See the full description on the dataset page: https://huggingface.co/datasets/BRlkl/samantha-r01-recursive-reasoning-corpus.Vinayak-Multistep-Recursive-Reasoning-Benchmark
Vinayak Multistep Recursive Reasoning Benchmark (VMRRB)
Overview
The Vinayak Multistep Recursive Reasoning Benchmark (VMRRB) is a large-scale prompt-based benchmark designed to evaluate advanced reasoning, recursive dependency resolution, encrypted task traversal, and robustness capabilities of frontier AI systems.
The benchmark evaluates a model's ability to:
Perform recursive multistep reasoning
Resolve interdependent question chains
Execute encrypted… See the full description on the dataset page: https://huggingface.co/datasets/SavantCapital/Vinayak-Multistep-Recursive-Reasoning-Benchmark.