datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.pinchbench-clawd-multi-step
PinchBench Clawd - Hirundo Format
Prepared from cptekur/pinchbench-clawd for Hirundo custom dataset loading.
Each source trajectory is expanded into one training row per assistant turn.
The question contains the prior user/assistant/tool context, and the answer
is the next assistant message including tool-call formatting.
Schema
system_prompt: Clawd system prompt with available tools.
question: Rendered context before the target assistant turn.
answer: The next… See the full description on the dataset page: https://huggingface.co/datasets/hirundo-io/pinchbench-clawd-multi-step.Multistepreasoningdecisionmaking
Reasoning Decision-Making Dataset
This dataset is designed to support training and evaluation of text generation models focused on reasoning, analysis, and decision-making tasks.
Dataset Structure
Each sample consists of two fields:
instruction: A prompt requiring reasoning, analysis, or decision-making
output: A structured and logical response to the instruction
Intended Use
This dataset is suitable for:
Instruction-following models
Reasoning and planning… See the full description on the dataset page: https://huggingface.co/datasets/yugi5/Multistepreasoningdecisionmaking.RAG_Planning_Multi_Step_Composition
🇰🇿 Kazakh Multi-Step Planning and Tool Composition Dataset
Dataset Summary
Kazakh Multi-Step Planning and Tool Composition Dataset is a Kazakh-language dataset for training and evaluating Large Language Models (LLMs) in agentic AI workflows that require multi-step planning, tool composition, and structured function calling.
The dataset contains user requests, available tool schemas, expected tool calls, simulated tool responses, and complete multi-turn… See the full description on the dataset page: https://huggingface.co/datasets/farabi-lab/RAG_Planning_Multi_Step_Composition.