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misa token head: +3,500 long agent-internal hard negatives
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---
license: cc-by-sa-4.0
language: [vi, en]
task_categories: [text-classification]
tags: [safety, guardrail, content-moderation, prompt-injection, jailbreak]
pretty_name: Qwen3.5-SafeProbe training data
extra_gated_prompt: "Access is granted manually for research on AI safety only. This dataset contains harmful, offensive and sexual text."
extra_gated_fields:
Affiliation: text
Intended use: text
---
# Qwen3.5-SafeProbe — training data
Training and held-out test data for [beyoru/Qwen3.5-SafeProbe-2B](https://huggingface.co/beyoru/Qwen3.5-SafeProbe-2B).
> ⚠️ Contains harmful, hateful, sexual and otherwise offensive text, collected for training safety classifiers.
| File | Rows | unsafe | safe |
|---|---|---|---|
| `misa/train.jsonl` | 31,832 | 11,117 | 20,715 |
| `misa/test.jsonl` | 3,565 | 1,315 | 2,250 |
| `standard/train.jsonl` | 71,774 | 29,257 | 42,517 |
| `standard/test.jsonl` | 7,908 | 3,287 | 4,621 |
| `misa/token_head_train.jsonl` | 12,000 | span-labelled long inputs + 3,500 long agent-internal prompts (safe, hard negatives) | |
| `standard/token_head_train.jsonl` | 8,500 | span-labelled long inputs | |
- `misa/`: MISA policy (Vietnamese law + enterprise-agent rules). `standard/`: public-benchmark convention.
- Row format: `{"id", "source", "label": "safe"|"unsafe", "messages": [OpenAI-style]}`; token-head rows add `unsafe_span` / `safe_span` (the inserted request inside a long input).
- Test splits are held out by scenario; training data was decontaminated against WildGuardTest, ToxicChat, OpenAI Moderation, Aegis 2.0, JBB, SimpleSafetyTests, XSTest and MultiJail.
Includes material derived from WildGuardMix (ODC-BY), Aegis 2.0 / Nemotron-Safety-Guard (CC-BY-4.0), Nailyk14/prompt-safety-multilingual-v2 (mixed, incl. CC-BY-SA-4.0) and WildChat (ODC-BY), plus synthetic and proprietary data.