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Datasets:
RegalFire
/
Agent-Failure-Recovery-Benchmark
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0
Tasks:
Reinforcement Learning
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
Tags:
agents
agentic-ai
benchmark
evaluation
reasoning
trajectories
+ 7
Libraries:
Datasets
pandas
Polars
+ 1
License:
mit
Dataset card
Data Studio
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Agent-Failure-Recovery-Benchmark
110 MB
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1 contributor
History:
3 commits
RegalFire
Release verified agent recovery benchmark with lossless Parquet viewer, evaluation interface and full metadata
a6e2a06
verified
about 22 hours ago
data
Release verified agent recovery benchmark with lossless Parquet viewer, evaluation interface and full metadata
about 22 hours ago
samples
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about 22 hours ago
validator
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.gitattributes
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COMMERCIAL_EXTENSION.md
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LICENSE
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MANIFEST.json
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PACKAGE_PROVENANCE.json
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QA_REPORT.md
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README.md
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SOURCE_LOCK.json
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THIRD_PARTY_LICENSES.md
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dataset.jsonl
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evaluate.py
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evaluation_smoke.json
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holdout.jsonl
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package_validation.json
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rejected.jsonl
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requirements.txt
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robustness_report.json
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schema.json
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serialization.json
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stats.json
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test.jsonl
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train.jsonl
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validation.jsonl
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validation_report.json
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