datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
arxiv_cplusplus_research_code
Dataset card for ArtifactAI/arxiv_cplusplus_research_code
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_cplusplus_research_code
Dataset Summary
ArtifactAI/arxiv_python_research_code contains over 10.6GB of source code files referenced strictly in ArXiv papers. The dataset serves as a curated dataset for Code LLMs.
How to use it
from datasets import load_dataset
# full dataset (10.6GB of data)
ds =… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_cplusplus_research_code.s2orc-cs-enriched
S2ORC CS Enriched
A Computer Science subset of the Semantic Scholar Open Research Corpus (S2ORC) enriched with LLM-generated structured metadata. Contains 1.1 million CS papers with extracted methods, models, datasets, metrics, compute estimates, and summaries.
Dataset Summary
Statistic
Value
Total papers
1,117,706
Total size
54.7 GB
Parquet files
1,118
Split
train
Dataset Structure
Base Columns
Content: parsed_title, abstract… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/s2orc-cs-enriched.arxiv_deep_learning_python_research_code_functions_summaries
Dataset Card for "AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries"
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries
Dataset Summary
AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries contains summaries for every python function and class extracted from source code files referenced in ArXiv papers. The… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries.arxiv_python_research_code
Dataset Card for "ArtifactAI/arxiv_python_research_code"
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_python_research_code
Dataset Summary
AlgorithmicResearchGroup/arxiv_python_research_code contains over 4.13GB of source code files referenced strictly in ArXiv papers. The dataset serves as a curated dataset for Code LLMs.
How to use it
from datasets import load_dataset
# full dataset (4.13GB of data)
ds =… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_python_research_code.arxiv_research_code
Dataset Card for "AlgorithmicResearchGroup/arxiv_research_code"
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_research_code
Dataset Summary
ArtifactAI/arxiv_research_code contains over 21.8GB of source code files referenced strictly in ArXiv papers. The dataset serves as a curated dataset for Code LLMs.
How to use it
from datasets import load_dataset
# full dataset (21.8GB of data)
ds =… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_research_code.arxiv_deep_learning_python_research_code
ArXiv Deep Learning Python Research Code
A curated corpus of Python source code files extracted from GitHub repositories referenced in ArXiv papers. Contains 391,496 files (1.49 GB) filtered to deep learning frameworks, designed for training and evaluating Code LLMs on research-grade code.
Dataset Summary
Statistic
Value
Total files
391,496
Total size
1.49 GB
Source repos
34,099
Time span
ArXiv inception through July 2023
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code.ArXivDLInstruct
Dataset Card for "AlgorithmicResearchGroup/arxiv_research_code"
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/ArXivDLInstruct
Dataset Summary
ArtifactAI/arxiv_research_code contains over 21.8GB of source code files referenced strictly in ArXiv papers. The dataset serves as a curated dataset for Code LLMs.
How to use it
from datasets import load_dataset
# full dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/ArXivDLInstruct.arxiv_java_research_code
Dataset Card for "arxiv_java_research_code"
More Information needed
s2orc-safety
S2ORC Safety
This dataset is a filtered and enriched subset of an S2ORC computer science paper corpus, focused on AI safety and adjacent safety-relevant research.
It contains 16,806 papers selected through:
local embedding generation
clustering
GPT-5.4 mini cluster-level screening
GPT-5.4 mini paper-level labeling
a rescue relabel pass on suspicious exclusions
structured metadata extraction over the accepted paper set
filtering out 304 rows that were missing both parsed_title and… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/s2orc-safety.gepa-rlm-exp-algorithmic-20260219-191545
gepa-rlm-exp-algorithmic-20260219-191545
GEPA prompt optimization experiment on AIME math problems.
Task LM: openai/gpt-4.1-mini | Reflection LM: openai/gpt-5 | Reflection Mode: algorithmic | Last updated: 2026-02-19 21:34 UTC
Results
Run
Method
k
Mode
Val Score
Test Acc
Tokens
Cost
Time
fixed_rlm_k20
rlm
20
algorithmic
48.89%
26.67%
932,391
$0.0000
5209s
Learning Curves
Experiment Config
{
"script_name": "run_experiment.py"… See the full description on the dataset page: https://huggingface.co/datasets/reasoning-degeneration-dev/gepa-rlm-exp-algorithmic-20260219-191545.gepa-exp-algorithmic-vanilla-20260220-083526
gepa-exp-algorithmic-vanilla-20260220-083526
GEPA prompt optimization experiment on AIME math problems.
Task LM: openai/gpt-4.1-mini | Reflection LM: openai/gpt-5 | Reflection Mode: algorithmic | Last updated: 2026-02-20 21:20 UTC
Results
Run
Method
k
Mode
Val Score
Test Acc
Tokens
Cost
Time
fixed_vanilla_k3
vanilla
3
algorithmic
35.56%
46.67%
77,464
$0.2182
3126s
Learning Curves
Experiment Config
{
"script_name":… See the full description on the dataset page: https://huggingface.co/datasets/reasoning-degeneration-dev/gepa-exp-algorithmic-vanilla-20260220-083526.Domain_Identification_Algorithms_Comparison_Datarepro-a-tight-theory-of-error-feedback-algorithms-in-distributed-optimization-traces
Agent traces
Agent sessions published from a Trackio Logbook.
douvras-algorithm-evolution-benchmark
Douvras Algorithm Evolution Benchmark v0.1
Synthetic candidate records with correctness, latency, memory and generation.
Candidates that fail correctness are invalid regardless of speed. It contains
48 records (32/8/8) across 12 workloads, split by workload.
Metrics are illustrative, not measured on real hardware. A real benchmark must
be run separately before claiming an optimization.
sorting_algorithm_3_pos_final1This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 10,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
8
],
"names": [
"panda_joint1",
"panda_joint2",
"panda_joint3",
"panda_joint4",
"panda_joint5",
"panda_joint6"… See the full description on the dataset page: https://huggingface.co/datasets/TimR643/sorting_algorithm_3_pos_final1.so101_act_algorithmThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 50,
"total_frames": 16126,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:50"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/omunaman/so101_act_algorithm.gepa-exp-algorithmic-rlm-20260220-083526
gepa-exp-algorithmic-rlm-20260220-083526
GEPA prompt optimization experiment on AIME math problems.
Task LM: openai/gpt-4.1-mini | Reflection LM: openai/gpt-5 | Reflection Mode: algorithmic | Last updated: 2026-02-20 21:25 UTC
Results
Run
Method
k
Mode
Val Score
Test Acc
Tokens
Cost
Time
fixed_rlm_k3
rlm
3
algorithmic
37.78%
44.00%
400,201
$0.0000
3483s
Learning Curves
Experiment Config
{
"script_name": "run_experiment.py"… See the full description on the dataset page: https://huggingface.co/datasets/reasoning-degeneration-dev/gepa-exp-algorithmic-rlm-20260220-083526.Sorting-Algorithms-Performance-Metrics
Sorting Algorithms Benchmark Dataset (Array Size: 1000)
A benchmark dataset comparing execution time, memory usage, and comparison counts of various sorting algorithms (Bubble Sort, Selection Sort, Insertion Sort, Merge Sort, Quick Sort, Heap Sort, Odd-Even Sort) on arrays of size 1000. Each algorithm was run 100 times with randomized inputs to ensure statistical significance.
Dataset Details
Columns
run: Trial number (1-100 per algorithm).
algorithm:… See the full description on the dataset page: https://huggingface.co/datasets/ismielabir/Sorting-Algorithms-Performance-Metrics.advanced-quantum-algorithms
Neura Parse — Advanced Quantum Algorithms: Derivations, QSVT/Block-Encoding & Hamiltonian Simulation
A derivation- and resource-analyzed algorithms vertical spanning the canonical fault-tolerant canon (with full proofs, complexity, and worked traces) and the modern QSVT/block-encoding toolkit through Hamiltonian simulation, amplitude estimation, and quantum linear systems. Turns the general dataset's one-topic-per-algorithm summaries into line-by-line derivations, lower… See the full description on the dataset page: https://huggingface.co/datasets/Neura-parse/advanced-quantum-algorithms.repro-convergence-rate-of-the-last-iterate-of-stochastic-proximal-algorithms-traces
Agent traces
Agent sessions published from a Trackio Logbook.
arxiv-beir-500k-generated-queries
Dataset Summary
A BEIR style dataset derived from ArXiv
Languages
All tasks are in English (en).
Dataset Structure
The dataset contains a corpus, queries and qrels (relevance judgments file). They must be in the following format:
corpus file: a .jsonl file (jsonlines) that contains a list of dictionaries, each with three fields _id with unique document identifier, title with document title (optional) and text with document paragraph or passage. For example:… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv-beir-500k-generated-queries.algorithm_selector_fjssp_3algo_3s_30s_predictionalgorithmic-sft-full-eval-v4
algorithmic-sft-full-eval-v4
Aggregate eval results: 10 models x 4 domains x 3 splits with bootstrap 95% CIs
Dataset Info
Rows: 42
Columns: 8
Columns
Column
Type
Description
model
Value('string')
HuggingFace model ID (LoRA adapter name)
domain
Value('string')
Task domain: formal_logic, conlang_morphology, cellular_automata, long_arithmetic
type
Value('string')
Training type: algo (algorithmic SFT) or distill (QwQ distillation)
split… See the full description on the dataset page: https://huggingface.co/datasets/raca-workspace-v1/algorithmic-sft-full-eval-v4.arxiv-beir-100k-generated-queriesaria-repo-benchmark
ARIA Repo Benchmark
The ARIA Repo Benchmark is part of the ARIA benchmark suite, a collection of closed-book benchmarks probing the ML knowledge that frontier models have internalized during training. This dataset contains 58 curated research paper implementations with metadata for evaluating whether ML experiments described in papers can be reproduced.
Dataset Summary
Size: 58 entries
Coverage: Computer Vision, NLP, Time Series, Graph, Bioinformatics
Purpose:… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/aria-repo-benchmark.aim-qwq-32b
Dataset Card for aim-qwq-32b
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/AlgorithmicOps/aim-qwq-32b/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicOps/aim-qwq-32b.r1-7b-distil
Dataset Card for r1-7b-distil
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/AlgorithmicOps/r1-7b-distil/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicOps/r1-7b-distil.aim-full-qwq-32b
Dataset Card for aim-full-qwq-32b
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/AlgorithmicOps/aim-full-qwq-32b/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicOps/aim-full-qwq-32b.aim-qwen2.5-7b-instruct-distil
Dataset Card for aim-qwen2.5-7b-instruct-distil
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/AlgorithmicOps/aim-qwen2.5-7b-instruct-distil/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicOps/aim-qwen2.5-7b-instruct-distil.algorithm_selector_fjssp_3algo_3s_30s_probability_lit