datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SVAMPmawps-asdiv-a_svamp
Dataset Card for "mawps-asdiv-a_svamp"
More Information needed
Calc-svamp
Dataset Card for Calc-SVAMP
Summary
The dataset is a collection of simple math word problems focused on arithmetics. It is derived from https://github.com/arkilpatel/SVAMP/.
The main addition in this dataset variant is the chain column. It was created by converting the solution to a simple html-like language that can be easily
parsed (e.g. by BeautifulSoup). The data contains 3 types of tags:
gadget: A tag whose content is intended to be evaluated by calling an external… See the full description on the dataset page: https://huggingface.co/datasets/MU-NLPC/Calc-svamp.svampsvamp
Dataset Card for "svamp"
More Information needed
svampprompted_svamp
Dataset Card for "prompted_svamp"
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cv_svamp_augmented_fold0
Dataset Card for "cv_svamp_augmented_fold0"
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SVAMPqwen-generated-svamp-controls-sft
Qwen-Generated SVAMP CoT Controls ? SFT
Qwen-generated controlled reasoning traces for SVAMP in LLaMA-Factory SFT format. Variants include ordinary, all-caps, no-comma, disclaimer, and multilingual examples.
Splits
3,940 training examples and 380 held-out evaluation examples.
Format
The JSON files use the LLaMA-Factory Alpaca-style schema. The included
dataset_info.json registers the exact training and evaluation names. DPO
records are marked with… See the full description on the dataset page: https://huggingface.co/datasets/akshay-sked/qwen-generated-svamp-controls-sft.task752_svamp_multiplication_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task752_svamp_multiplication_question_answering
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task752_svamp_multiplication_question_answering.svamptask753_svamp_addition_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task753_svamp_addition_question_answering
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task753_svamp_addition_question_answering.task754_svamp_common-division_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task754_svamp_common-division_question_answering
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task754_svamp_common-division_question_answering.task751_svamp_subtraction_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task751_svamp_subtraction_question_answering
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task751_svamp_subtraction_question_answering.X-SVAMP_en_zh_ko_it_es
X-SVAMP
🤗 Paper | 📖 arXiv
Dataset Description
X-SVAMP is an evaluation benchmark for multilingual large language models (LLMs), including questions and answers in 5 languages (English, Chinese, Korean, Italian and Spanish).
It is intended to evaluate the math reasoning abilities of LLMs. The dataset is translated by GPT-4-turbo from the original English-version SVAMP.
In our paper, we evaluate LLMs in a zero-shot generative setting: prompt the instruction-tuned LLM with… See the full description on the dataset page: https://huggingface.co/datasets/zhihz0535/X-SVAMP_en_zh_ko_it_es.svampsvamp with rationale
SDS_train_svampdisentangled-svamp
Dataset Overview
This dataset accompanies the EMNLP 2025 paper “Can LLMs Reason Abstractly Over Math Word Problems Without CoT? Disentangling Abstract Formulation From Arithmetic Computation.” It is designed to separate two capabilities in math word problems:
Abstract formulation (deriving the correct expression, symbolic or numerical form)
Arithmetic computation (evaluating a given expression)
To do this, we created four evaluation settings: original, symbolic abstraction… See the full description on the dataset page: https://huggingface.co/datasets/Disentangled-Math-Reasoning/disentangled-svamp.qwen-generated-svamp-controls-dpo
Qwen-Generated SVAMP CoT Controls ? DPO
Preference pairs built from Qwen-generated SVAMP reasoning traces in LLaMA-Factory DPO format. Each record contains instruction, input, chosen, and rejected fields.
Splits
3,152 training preference pairs and 304 held-out evaluation pairs.
Format
The JSON files use the LLaMA-Factory Alpaca-style schema. The included
dataset_info.json registers the exact training and evaluation names. DPO
records are marked with… See the full description on the dataset page: https://huggingface.co/datasets/akshay-sked/qwen-generated-svamp-controls-dpo.cv_svamp_augmented_fold1
Dataset Card for "cv_svamp_augmented_fold1"
More Information needed
SVAMP_de
SVAMP_de: A Translated German Math Dataset
This is a high-quality German translation of the SVAMP dataset.
We employed a State-of-the-Art (SOTA) LLM within a strict validation pipeline to ensure 100% numerical consistency and logical fidelity.
Math word problems rely on precise numbers and logic. Standard translations often hallucinate numbers or mangle units.
SVAMP_de was generated with a "Strict Logic" pipeline:
Translation: Using SOTA LLMs.
Validation: Every single row was… See the full description on the dataset page: https://huggingface.co/datasets/tabularisai/SVAMP_de.bad_data_gsm8k_svamp.csvSome bad data discovered in the popular GSM8K and SVAMP LLM benchmarking datasets.
These examples have incorrect answers in the corresponding math problem benchmark dataset, and should not be used to evaluate AI models.
We detected this bad data automatically using Cleanlab's Trustworthy Language Model. TLM's estimated trustworthiness score for each example is also provided.
Example error found in the GSM8K dataset:
Question: After scoring 14 points, Erin now has three times… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/bad_data_gsm8k_svamp.csv.svampsvamp
svamp — evaluation data (OpenCompass format)
Bud Ecosystem eval mirror. OpenCompass-format evaluation data for svamp, for offline reproducible model evaluation (config svamp_gen). Original source: https://github.com/arkilpatel/SVAMP — license MIT, unchanged; all rights remain with the original authors.
cv_svamp_augmented_fold2
Dataset Card for "cv_svamp_augmented_fold2"
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svamp_objective_examplessvamp_optimize_examplescv_svamp_augmented_fold3_ver2
Dataset Card for "cv_svamp_augmented_fold3_ver2"
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cv_svamp_augmented_fold3
Dataset Card for "cv_svamp_augmented_fold3"
More Information needed