Benchmark

HEST-Benchmark

HEST-Benchmark tests prediction of gene expression from histological image representations.

Sources

mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes

100 evaluations · 100 results

Overview

Datasets

Paired spatial-transcriptomic measurements and histology images from HEST resources.

Sources

mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes

Metrics

Pearson correlation between predicted and measured log1p gene expression, using the 50 genes with highest normalized variance.

Sources

hest primary benchmark evidence · Sections 5.1–5.2; Appendix Table A11

Allowed inputs

Histology patches for prediction; spatial expression supplies evaluation labels.

Sources

mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes

Evaluation procedure diagram

How it worksEvaluation procedure

Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions.

Sources (2)

mahmoodlab/HEST official source; hest primary benchmark evidence · Pinned README: HEST-Benchmark overview; evaluation notes; Sections 5.1–5.2; Appendix Table A11

Source reviewed · Automated source review, 2026-09-16. All specifications and missing details

Results

Each comparison retains its reviewed evaluation scope, dataset and metric. Results are shown without a pooled ranking.

Evaluation scope and datasetMetric and reported setup

HEST-Benchmark CCRCC: Gene expression prediction from histology, Clear cell renal cell carcinoma

pearson_r (correlation) · Higher values are better.

HEST-Benchmark CCRCC: Gene expression prediction from histology, Clear cell renal cell carcinoma · HEST-Benchmark CCRCC (HEST-Benchmark split)

Evidence origin: Author-reported evaluation.

HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis · Table 1, row(CCRCC)

Every figure comes from the same Random Forest head over frozen features, so it measures the encoder, not a full prediction pipeline.
Cohorts differ in size and difficulty, so a figure in one cohort is not comparable to a figure in another.

Comparison details and limitations

Every method HEST-Benchmark reports on Gene expression prediction from histology, Clear cell renal cell carcinoma, scored with Pearson correlation on HEST-Benchmark CCRCC.

Author-reported numbers, source checked but not independently reproduced.

Automated source review: 2026-09-18. Numerical source review does not establish independent reproduction.

Dots show point estimates. Whiskers show only explicitly defined uncertainty (standard deviation, standard error or a labelled interval); their definitions remain in Table. Unresolved uncertainty is not plotted. Differences do not establish statistical significance.

Find a tested model or method

Showing 10 of 10 matching rows.

Zoom to observed range

Tested configuration

-1-0.500.51

Reported score

Methods and evaluation design

Procedure, tasks and evaluated configurations

How it works

Evaluation methodology

HEST-Benchmark connects histology patches to spatially measured gene expression. A patch encoder supplies features to a regression model, which predicts highly variable genes. Patient-stratified folds evaluate transfer between individuals, and correlation is summarized across those folds.

Sources

hest primary benchmark evidence · Sections 5.1–5.2; Appendix Table A11

Evaluation design

Benchmarks bring together tasks and protocols. A task describes the biological question; a protocol defines a particular test.

Tasks

These source-backed links do not make different protocols or scores interchangeable.

Baseline coverage

Reference methods help show what a model adds beyond simple controls. We track a null control and a conventional method for each protocol.

No concrete protocols are explicitly linked to this suite. Protocol identification and baseline selection are outstanding.

Protocol coverage CSV · Model evaluation matrix · Source table · Release and checksums

Coverage is derived from release 2026-09-29-06401fd5b220. Source citations describe the original records; they do not validate an unreviewed baseline proposal. No results have been generated by this audit.

Run this benchmark

Install HEST and run the benchmark

Install the library with its benchmark extras, then evaluate a patch encoder across the ten cohorts on this page.

Generate predictions and evaluate them. This recipe does not establish reproduction of a particular published score.

Dataset access: HEST-1k, downloaded by the library.
Model and weights: A published patch encoder checkpoint.
Licences: Project licence: see repository. Upstream data licences are separate and unreported here.
Software: Python with the repository installed in editable mode and its benchmark extras.
Hardware: Not stated in the cited section. Several of these steps expect a GPU.

Required inputs and expected outputs

Inputs

A histology patch encoder.

Outputs

Per-cohort Pearson correlation from the benchmark's own head.

Execution steps

1. Install (Command line)
Source reviewed; these instructions have not been executed by rewire.
```
git clone https://github.com/mahmoodlab/HEST.git
cd HEST
conda create -n "hest" python=3.11
conda activate hest
pip install -e .
```
HEST: repository README · README.md at 3ddb5eaf, HEST-Library installation, lines 46-50
2. Add the benchmark extras (Command line)
Source reviewed; these instructions have not been executed by rewire.
```
pip install -e ".[benchmark]"
```
HEST: repository README · README.md at 3ddb5eaf, Additional dependencies (HEST-Benchmark), lines 56-56
3. Inspect the data (Python)
Source reviewed; these instructions have not been executed by rewire.
```
from hest import iter_hest

for st in iter_hest('../hest_data', id_list=['TENX95']):
    print(st)
```
HEST: repository README · README.md at 3ddb5eaf, Inspect HEST-1k with HEST-Library, lines 80-83

Use your own model

Run your model locally and return predictions keyed by the input IDs. The evaluator supplies biological inputs without test labels and owns scoring. This interface is not a sandbox for model code.

Pass your existing prediction function into this adapter. Its output direction must match the selected protocol.

class MyModelAdapter:
    def __init__(self, score):
        self.score = score

    def predict(self, inputs):
        return {row["id"]: float(self.score(row)) for row in inputs}

# adapter = MyModelAdapter(your_prediction_function)
# report = rewirebench.run(prepared, adapter, output="runs/my-model")

Alternatively, generate a keyed prediction file in your existing model environment and use the score-only recipe. Your model code and weights do not need to be shared.

HEST: repository README · README.md at 3ddb5eaf

Scope and limitations

Quoted from the project's README and not executed by rewire, so the commands are evidence of what the project documents rather than a verified run.
The project may have changed since the pinned commit.
Every figure comes from the same Random Forest head, so it measures the encoder rather than a full pipeline.
Cohorts differ in size and difficulty and are not comparable to each other.

Contribute a result for review. The library can submit an exported evaluation for private review when intake is open. Check the contribution page for access and sign-in.

Original repository instructions

Run this benchmark

Official installation, benchmark extras and a dedicated HEST-Benchmark notebook are linked. The complete HEST-1k collection is described as exceeding 1 TB; select the benchmark subset and patch encoder deliberately. This pass does not promote dataset download or WSI preparation into a model evaluation command.

A maintained rewire runner has not been verified for this benchmark. Check data access, weights, licences, dependencies and hardware in the linked official documentation; requirements have not been fully extracted.

mahmoodlab/HEST / README.md · README.md lines 36–73 and 137–139 (Data, installation and benchmarking your own model)

Strengths, limitations and unresolved questions

Strengths and limitations

Strengths supported by sources

Paired measurements connect image representations to molecular rather than image-only labels.
Sources
mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes

Limitations and conditions

The input is an image, but the evaluated output is spatial molecular expression. The selected genes, regression head and patient partitions are essential comparison conditions.
Sources
hest primary benchmark evidence · Sections 5.1–5.2; Appendix Table A11

Profile review details

Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction.

Stable record: discovery-benchmark-hest-benchmark

Specifications

Inputs, training, access and other details

Explanatory profile: source reviewed · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Data, procedure and scoring
Property	Description and evidence
Datasets	Paired spatial-transcriptomic measurements and histology images from HEST resources. Sources mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes
Splits	Patient-stratified cross-validation: one fold per patient, except ccRCC uses half as many folds because of its larger patient cohort. Sources hest primary benchmark evidence · Sections 5.1–5.2; Appendix Table A11
Metrics	Pearson correlation between predicted and measured log1p gene expression, using the 50 genes with highest normalized variance. Sources hest primary benchmark evidence · Sections 5.1–5.2; Appendix Table A11
Baselines	Ridge regression on PCA-reduced embeddings is the reported comparison setup. Sources mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes
Leakage controls	All samples from a patient stay within their fold, preventing patch-level mixing of the same patient between training and test. Histology-encoder pretraining overlap is a separate concern. Sources hest primary benchmark evidence · Sections 5.1–5.2; Appendix Table A11
Uncertainty	The paper reports the mean and standard deviation across folds or patients, not a universal retraining-seed interval. Sources hest primary benchmark evidence · Sections 5.1–5.2; Appendix Table A11
Entity type	Spatial-transcriptomics prediction benchmark. Sources mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes
Organisms	Multiple species selectable in the HEST metadata. Sources mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes
Assays	Paired tissue histology and spatial gene-expression measurements. Sources mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes
Allowed inputs	Histology patches for prediction; spatial expression supplies evaluation labels. Sources mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes
Adaptation	Patch embeddings are evaluated through downstream expression prediction. Sources mahmoodlab/HEST official source · Pinned README: HEST-Benchmark overview; evaluation notes

Applicable tests and references

Applicability is distinct from a completed evaluation.

Spatial expression ridge regression · proposed

Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Papers and result coverage

Last literature check: 2026-09-17. Primary-source discovery and table/protocol screening; source checked is not independently reproduced. Raw acquisitions not automatically numerical publication approval.

Paper or primary resource	Version	Reference
HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis	Version pinned by URL and artifact SHA256 when available	Read source

Historical gaps recorded on 2026-09-17

The catalogue now holds 100 result rows for this benchmark. A note below about pending extraction describes the state on 2026-09-17 and may since have been answered by a later batch. The result rows and their sources are the current record.

New web search finds updated official benchmark inventory; current README values cannot be assigned to original v 1 paper configurations. Fresh PDF retrieval failed; cached pinned v 1 PDF preserved. Complete table extraction remains pending.

Search and extraction details

source found structured extraction pending

Searches

HEST-Benchmark primary paper benchmark results

Evidence locations

arXiv2406.16192v1; HEST-Benchmark results and cross-validation procedure

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

29 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
Property and statement	Original source and location	Review and provenance
Diagram caption Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions. Individual claims	hest primary benchmark evidence Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes; Sections 5.1–5.2; Appendix Table A11 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2406.16192v1 Retrieved: 2026-09-16T21:05:00.540640+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `636099a73dee8337f60e6e9120230b914605b35553872ddf76e4661bbe14be9b` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram caption Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions. Individual claims	mahmoodlab/HEST official source Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes; Sections 5.1–5.2; Appendix Table A11 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3 Retrieved: 2026-09-16T10:30:22.733154+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `3d002564045d3c493f30386df7983ee34b0f2f7ac89bf32ac63a5f780395d811` Hash scope: Hash scope not separately documented; inspect source record
Diagram steps Allowed inputs: Histology patches for prediction; spatial expression supplies evaluation labels. Splits: Patient-stratified cross-validation: one fold per patient, except ccRCC uses half as many folds because of its larger patient cohort. Metrics: Pearson correlation between predicted and measured log1p gene expression, using the 50 genes with highest normalized variance. Individual claims	hest primary benchmark evidence Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes; Sections 5.1–5.2; Appendix Table A11 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2406.16192v1 Retrieved: 2026-09-16T21:05:00.540640+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `636099a73dee8337f60e6e9120230b914605b35553872ddf76e4661bbe14be9b` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram steps Allowed inputs: Histology patches for prediction; spatial expression supplies evaluation labels. Splits: Patient-stratified cross-validation: one fold per patient, except ccRCC uses half as many folds because of its larger patient cohort. Metrics: Pearson correlation between predicted and measured log1p gene expression, using the 50 genes with highest normalized variance. Individual claims	mahmoodlab/HEST official source Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes; Sections 5.1–5.2; Appendix Table A11 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3 Retrieved: 2026-09-16T10:30:22.733154+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `3d002564045d3c493f30386df7983ee34b0f2f7ac89bf32ac63a5f780395d811` Hash scope: Hash scope not separately documented; inspect source record
Diagram title Evaluation procedure Individual claims	hest primary benchmark evidence Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes; Sections 5.1–5.2; Appendix Table A11 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2406.16192v1 Retrieved: 2026-09-16T21:05:00.540640+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.diagram.title` Source artifact SHA-256: `636099a73dee8337f60e6e9120230b914605b35553872ddf76e4661bbe14be9b` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram title Evaluation procedure Individual claims	mahmoodlab/HEST official source Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes; Sections 5.1–5.2; Appendix Table A11 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3 Retrieved: 2026-09-16T10:30:22.733154+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.diagram.title` Source artifact SHA-256: `3d002564045d3c493f30386df7983ee34b0f2f7ac89bf32ac63a5f780395d811` Hash scope: Hash scope not separately documented; inspect source record
Datasets Paired spatial-transcriptomic measurements and histology images from HEST resources. Individual claims	mahmoodlab/HEST official source Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes Version: 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3 Retrieved: 2026-09-16T10:30:22.733154+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.facts.0.value` Source artifact SHA-256: `3d002564045d3c493f30386df7983ee34b0f2f7ac89bf32ac63a5f780395d811` Hash scope: Hash scope not separately documented; inspect source record
Splits Patient-stratified cross-validation: one fold per patient, except ccRCC uses half as many folds because of its larger patient cohort. Individual claims	hest primary benchmark evidence Original source ↗ Sections 5.1–5.2; Appendix Table A11 Version: 2406.16192v1 Retrieved: 2026-09-16T21:05:00.540640+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.facts.1.value` Source artifact SHA-256: `636099a73dee8337f60e6e9120230b914605b35553872ddf76e4661bbe14be9b` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Adaptation Patch embeddings are evaluated through downstream expression prediction. Individual claims	mahmoodlab/HEST official source Original source ↗ Pinned README: HEST-Benchmark overview; evaluation notes Version: 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3 Retrieved: 2026-09-16T10:30:22.733154+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.facts.10.value` Source artifact SHA-256: `3d002564045d3c493f30386df7983ee34b0f2f7ac89bf32ac63a5f780395d811` Hash scope: Hash scope not separately documented; inspect source record
Metrics Pearson correlation between predicted and measured log1p gene expression, using the 50 genes with highest normalized variance. Individual claims	hest primary benchmark evidence Original source ↗ Sections 5.1–5.2; Appendix Table A11 Version: 2406.16192v1 Retrieved: 2026-09-16T21:05:00.540640+00:00	source checked automated source review · 2026-09-16 Audit details Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: `attributes.profile.facts.2.value` Source artifact SHA-256: `636099a73dee8337f60e6e9120230b914605b35553872ddf76e4661bbe14be9b` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Sources and history

View linked audit checks and correction history

Release 2026-09-29-06401fd5b220 · Record review: discovered

5 source records and release history

mahmoodlab/HEST official source · Original source · 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3
HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis · Original source · Version pinned by URL and artifact SHA256 when available
mahmoodlab/HEST / README.md · Original source · Git commit 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3
HEST: repository README · Original source · 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3
hest primary benchmark evidence · Original source · 2406.16192v1

Download this release

Technical metadata and extraction receipts

Stable ID: discovery-benchmark-hest-benchmark

areas: spatial-omics
entity level: suite
scope note: Specialist molecular or omics evaluation; protocol details require review before numerical comparison.
task: Gene expression prediction from matched histology
version: Not reported
benchmark research: review date: 2026-09-17; status: source_found_structured_extraction_pending; primary sources: evidence-expansion-p2-hest-cached-636099a73dee; inspected locators: arXiv2406.16192v1; HEST-Benchmark results and cross-validation procedure; searched queries: HEST-Benchmark primary paper benchmark results; gaps: New web search finds updated official benchmark inventory; current README values cannot be assigned to original v 1 paper configurations. Fresh PDF retrieval failed; cached pinned v 1 PDF preserved. Complete table extraction remains pending.; claim scope: Primary-source discovery and table/protocol screening; source checked is not independently reproduced. Raw acquisitions not automatically numerical publication approval.
historical missing metadata: dataset release: unextracted; metric implementation: unextracted; split manifest: unextracted; version: unextracted
metadata review scope: historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
entity classification: review date: 2026-09-17; rationale: The cited profile describes a collection of evaluation tasks or protocols; retain it as the top-level benchmark suite. Its datasets and individual protocols remain separate records.; source ids: src-discovery-mahmoodlab-hest; source locator: Pinned README: HEST-Benchmark overview; evaluation notes; ambiguities: None recorded
run documentation: record id: discovery-benchmark-hest-benchmark; source ids: run-doc-hest-benchmark-readme-md-3ddb5eaf; status: official_documentation_linked; summary: Official installation, benchmark extras and a dedicated HEST-Benchmark notebook are linked. The complete HEST-1k collection is described as exceeding 1 TB; select the benchmark subset and patch encoder deliberately. This pass does not promote dataset download or WSI preparation into a model evaluation command.; source locator: README.md lines 36–73 and 137–139 (Data, installation and benchmarking your own model)
run recipes: id: hest-official; protocol id: discovery-benchmark-hest-benchmark; version: 3ddb5eaf5bd2a8133e0c0e8015816489a3d99dc3; title: Install HEST and run the benchmark; purpose: generate_and_evaluate; summary: Install the library with its benchmark extras, then evaluate a patch encoder across the ten cohorts on this page.; inputs: A histology patch encoder.; outputs: Per-cohort Pearson correlation from the benchmark's own head.; requirements: data: HEST-1k, downloaded by the library.; weights: A published patch encoder checkpoint.; licence: Project licence: see repository. Upstream data licences are separate and unreported here.; software: Python with the repository installed in editable mode and its benchmark extras.; hardware: Not stated in the cited section. Several of these steps expect a GPU.; instructions: runtime: command_line; title: Install; code: git clone https://github.com/mahmoodlab/HEST.git cd HEST conda create -n "hest" python=3.11 conda activate hest pip install -e .; status: source_reviewed_not_executed; source ids: project-recipe-hest-3ddb5eaf; source locator: README.md at 3ddb5eaf, HEST-Library installation, lines 46-50; runtime: command_line; title: Add the benchmark extras; code: pip install -e ".[benchmark]"; status: source_reviewed_not_executed; source ids: project-recipe-hest-3ddb5eaf; source locator: README.md at 3ddb5eaf, Additional dependencies (HEST-Benchmark), lines 56-56; runtime: python; title: Inspect the data; code: from hest import iter_hest for st in iter_hest('../hest_data', id_list=['TENX95']): print(st); status: source_reviewed_not_executed; source ids: project-recipe-hest-3ddb5eaf; source locator: README.md at 3ddb5eaf, Inspect HEST-1k with HEST-Library, lines 80-83; limitations: Quoted from the project's README and not executed by rewire, so the commands are evidence of what the project documents rather than a verified run.; The project may have changed since the pinned commit.; Every figure comes from the same Random Forest head, so it measures the encoder rather than a full pipeline.; Cohorts differ in size and difficulty and are not comparable to each other.; source ids: project-recipe-hest-3ddb5eaf; source locator: README.md at 3ddb5eaf

Related records

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Overview

Datasets

Metrics

Allowed inputs

Results

Methods and evaluation design

How it works

Evaluation design

Tasks

Baseline coverage

Run this benchmark

Install HEST and run the benchmark

Inputs

Outputs

Execution steps

1. Install (Command line)

2. Add the benchmark extras (Command line)

3. Inspect the data (Python)

Run this benchmark

Strengths and limitations

Strengths supported by sources

Limitations and conditions

Specifications

Evidence

Papers and result coverage

Searches

Evidence locations

Evidence table

Sources and history