datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ScalpelBench
ScalpelBench
ScalpelBench is a compact instruction-tuning corpus developed for controlled
studies of model compression, with a particular focus on layer pruning,
post-pruning recovery, and capability retention. The released corpus contains
approximately 0.1B tokens of instruction-response data spanning general
English, Chinese, mathematical reasoning, and code generation.
Mixture Design
The mixture proportions follow high-level capability-balancing principles… See the full description on the dataset page: https://huggingface.co/datasets/freeai-org/ScalpelBench.Semigroup_Reasoning_Model_A_Scalpel
Semigroup Reasoning Model: A Scalpel
Formalizing Sparse Neural Circuits as Reasoning Dynamics
🎯 Central Question
How do we formalize the interpretability of reasoning processes?
This work establishes reasoning as a semigroup dynamical system, providing the first formal equivalence between sparse neural circuits and algebraic reasoning dynamics. We prove that:
Reasoning is a semigroup orbit problem, not a vector space embedding task.
🔬 Key Contributions… See the full description on the dataset page: https://huggingface.co/datasets/OzTianlu/Semigroup_Reasoning_Model_A_Scalpel.