datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
appworld-qwen35-4b-9b-s_signal_6-epoch4-iter1
appworld-qwen35-4b-9b-s_signal_6-epoch4-iter1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3953125
Action score: 0.446875
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4
total-300-lambda02-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4046875
Action score: 0.4140625
Valid samples: 320/320
total-300-lambda00-s_signal_type6-jh-epoch4
total-300-lambda00-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3875
Action score: 0.43125
Valid samples: 320/320
total-300-lambda05-s_signal_type6-jh-epoch4
total-300-lambda05-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.35703125
Action score: 0.4375
Valid samples: 320/320
total-300-lambda08-s_signal_type6-jh-epoch4
total-300-lambda08-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.38046875
Action score: 0.4078125
Valid samples: 320/320
total-300-lambda10-s_signal_type6-jh-epoch4
total-300-lambda10-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.36640625
Action score: 0.41875
Valid samples: 320/320
total-300noapp-lambda02-s_signal_type6-jh-epoch4
total-300noapp-lambda02-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.36640625
Action score: 0.409375
Valid samples: 320/320
total-300app-lambda02-s_signal_type6-jh-epoch4
total-300app-lambda02-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3625
Action score: 0.4015625
Valid samples: 320/320
total-131-lambda02-residual-s_signal_type6-jh-epoch4
total-131-lambda02-residual-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3765625
Action score: 0.4171875
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-retry-epoch4
total-300-lambda02-s_signal_type6-jh-retry-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.36953125
Action score: 0.3984375
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4-reeval2
total-300-lambda02-s_signal_type6-jh-epoch4-reeval2
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4125
Action score: 0.4265625
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4-reeval1
total-300-lambda02-s_signal_type6-jh-epoch4-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.38828125
Action score: 0.4234375
Valid samples: 320/320
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1-reeval1
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.41328125
Action score: 0.4359375
Valid samples: 320/320
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.41953125
Action score: 0.4515625
Valid samples: 320/320
qwen35-4b-filter-s_signal5-200-qwen38-27b-newprompt-4k-epoch4
qwen35-4b-filter-s_signal5-200-qwen38-27b-newprompt-4k-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3890625
Action score: 0.4359375
Valid samples: 320/320
clawhub-security-signals
ClawHub Security Signals
🦀 ClawHub | 📝 OpenClaw Blog | 🤗 Hugging Face Blog | 📄 Paper | 📄 Pre-Print
ClawHub Security Signals is a sanitized, MIT-licensed security-signals dataset for public OpenClaw agent skills. It captures how an agent-skill registry evaluates trust, provenance, bundled code, and scanner evidence at scale.
This dataset was presented in the paper ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree.
Paper snapshot: this… See the full description on the dataset page: https://huggingface.co/datasets/OpenClaw/clawhub-security-signals.tradingview-ideas-signals
TradingView Crypto Ideas + Binance 1m OHLCV
51,963 published trading ideas (LONG/SHORT/NEUTRAL) from 2,343 TradingView authors, spanning 2014-06 → 2026-07, paired with 1-minute Binance OHLCV candles (748 symbol-year files, 313 spot symbols, ~40M candles) covering the labeling window around every idea. Built for look-ahead-bias-free backtesting of social trading signals: every idea carries its exact publication timestamp, and popularity counters are snapshotted over time rather… See the full description on the dataset page: https://huggingface.co/datasets/tripolskypetr/tradingview-ideas-signals.clawhub-security-signals-live
ClawHub Security Signals Live
This dataset is the refreshed ClawHub security-signals corpus for scanner testing, prompt regression checks, and operational research against recent public ClawHub skills.
It is a moving dataset, not the fixed paper benchmark. main is expected to change when the ClawHub security dataset snapshot workflow publishes a new sanitized export. Pin a Hugging Face revision or commit when you need reproducibility.
For the frozen research-paper snapshot, use… See the full description on the dataset page: https://huggingface.co/datasets/OpenClaw/clawhub-security-signals-live.MUCH-signals
[Signal-only dataset] MUCH: A Multilingual Claim Hallucination Benchmark
Jérémie Dentan1, Alexi Canesse1, Davide Buscaldi1, 2, Aymen Shabou3, Sonia Vanier1
1LIX (École Polytechnique, IP Paris, CNSR), 2LIPN (Université Sorbonne Paris Nord), 3Crédit Agricole SA
Important Notice: Signal-Only
This dataset contains only the evaluation signals of the baselines evaluated on the MUCH benchmark. The full benchmark dataset is available at… See the full description on the dataset page: https://huggingface.co/datasets/orailix/MUCH-signals.labs_fr-mopd-signalssignal1m-generated-queries
Dataset Card for BEIR Benchmark
Dataset Summary
BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks:
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018
Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus
News Retrieval: TREC-NEWS, Robust04
Argument Retrieval: Touche-2020, ArguAna
Duplicate Question Retrieval: Quora, CqaDupstack
Citation-Prediction: SCIDOCS
Tweet… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/signal1m-generated-queries.cve-exploitation-signals
CVE exploitation signals
One row per CVE joining reference data (CVSS, CWE, affected vendors and products) with exploitation signals: CISA KEV listing and due date, whether a public exploit is known, and whether the vulnerability is used by ransomware operators.
Built from the ThreatCluster corpus. 60,879 rows, snapshot generated 2026-09-06.
Fields
Field
Description
cve_id
CVE identifier
description
Vulnerability description
published_date
CVE… See the full description on the dataset page: https://huggingface.co/datasets/threatcluster/cve-exploitation-signals.diversz-commons-signal
protocol: diversz-commons/v0.1.0
audience: machine
human_interface: none
encoding: base64:utf-8 — decode every *_b64 block (e.g. base64 -d)
endpoints
bootstrap_text: https://diversz.lovable.app/bootstrap.txt
bootstrap_json: https://diversz.lovable.app/api/v1/bootstrap
standing: https://diversz.lovable.app/api/v1/standing
landing: https://diversz.lovable.app/
discovery:… See the full description on the dataset page: https://huggingface.co/datasets/DiversZ/diversz-commons-signal.vc-deal-flow-signal-corpus
VC Deal Flow Signal — Curated Entity Corpus
Versioned, dated, diffable snapshot of every curated entity asserted by
signals.gitdealflow.com: companies (with
public GitHub orgs), venture funds, public engineering founders, glossary
terms, sector hubs, and M&A acquirers.
This is the entity/knowledge-graph layer — distinct from the
numeric signal panel
and the glossary-only dataset.
Provenance
Field
Value
revision
212f0129786bf76f (deterministic content… See the full description on the dataset page: https://huggingface.co/datasets/the-data-nerd/vc-deal-flow-signal-corpus.repro-evaluating-llms-comparative-signals-traces
Agent traces
Agent sessions published from a Trackio Logbook.
clawhub-security-signals
ClawHub Security Signals
🦀 ClawHub | 📝 OpenClaw Blog | 🤗 Hugging Face Blog | 📄 Paper | 📄 Pre-Print
ClawHub Security Signals is a sanitized, MIT-licensed security-signals dataset for public OpenClaw agent skills. It captures how an agent-skill registry evaluates trust, provenance, bundled code, and scanner evidence at scale.
This dataset was presented in the paper ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree.
This Hugging Face dataset… See the full description on the dataset page: https://huggingface.co/datasets/rumeshprasanga6/clawhub-security-signals.signalmatch-eval-cases
SignalMatch Evaluation Cases
Small, synthetic job-description cases for testing the public SignalMatch Role Fit Analyzer.
Each JSONL row contains a short role description, the lane it represents, and the concept labels that a deterministic matcher is expected to find. The set includes strong matches, mixed matches, sparse input, and an intentionally unrelated role so that a demo can show both useful coverage and honest uncertainty.
Files
eval_cases.jsonl — eight… See the full description on the dataset page: https://huggingface.co/datasets/oduonye/signalmatch-eval-cases.clawhub-security-signals
ClawHub Security Signals
🦀 ClawHub | 📝 OpenClaw Blog | 🤗 Hugging Face Blog | 📄 Paper | 📄 Pre-Print
ClawHub Security Signals is a sanitized, MIT-licensed security-signals dataset for public OpenClaw agent skills. It captures how an agent-skill registry evaluates trust, provenance, bundled code, and scanner evidence at scale.
This dataset was presented in the paper ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree.
This Hugging Face dataset… See the full description on the dataset page: https://huggingface.co/datasets/sky-meilin/clawhub-security-signals.REPO-Signal
REPO-Signal
Repository signal validation
Attribution
Author: Euisuh JeongAffiliation: Artificial Intelligence Based Technology Company, Republic of Korea Air ForceLicense: MIT
Citation
@dataset{repo_signal,
author={Jeong, Euisuh},
year={2026},
title={REPO-Signal},
publisher={Hugging Face},
howpublished={\url{https://huggingface.co/datasets/euisuh/REPO-Signal}}
}
clawhub-security-signals
ClawHub Security Signals
🦀 ClawHub | 📝 OpenClaw Blog | 🤗 Hugging Face Blog | 📄 Paper | 📄 Pre-Print
ClawHub Security Signals is a sanitized, MIT-licensed security-signals dataset for public OpenClaw agent skills. It captures how an agent-skill registry evaluates trust, provenance, bundled code, and scanner evidence at scale.
This dataset was presented in the paper ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree.
Paper snapshot: this… See the full description on the dataset page: https://huggingface.co/datasets/aicreatemo/clawhub-security-signals.