# 蚂蚁 inclusionAI 发布 Step-3.7-Flash-singprobe：基于隐藏状态的流式安全探针

- 来源：蚂蚁 inclusionAI：HuggingFace 新模型
- 发布时间：2026-09-14 11:20
- AIHOT 分数：44
- AIHOT 链接：https://aihot.news/items/cmu0zy4y307ifro2nenigu700
- 原文链接：https://huggingface.co/inclusionAI/Step-3.7-Flash-singprobe

## AI 摘要

蚂蚁 inclusionAI 发布 Step-3.7-Flash-singprobe，这是一个构建在 stepfun-ai/Step-3.7-Flash 上的流式安全探针，仅 8.13M 参数，复用基座模型隐藏状态对每个 token 的查询意图、回复不安全和幻觉风险打分，解码开销低于 0.5%。

## 正文

Model Description

SingProbe is an intrinsic streaming guardrail built on stepfun-ai/Step-3.7-Flash. Rather than running a separate safety model, this lightweight probe reuses the base model's hidden states during generation to score, at every token, query intent, response unsafety, and hallucination risk. It adds less than 0.5% decode-time overhead.

Base model Probe parameters Tapped layers Outputs

inclusionAI/Step-3.7-Flash-singprobe 8.13M [13, 28, 43] 8 intents + unsafe + hallucination

See the technical report for methodology and complete results. Training codes are available at inclusionAI/SingProbe.

Evaluation

Higher is better for every metric. Results are averages over the benchmark suites specified below.

Task Metric Step-3.7-Flash-singprobe Reference baseline

Query intent classification (6 benchmarks) F1 0.8502 YuFeng-XGuard-Reason-8B: 0.8714

Response safety classification (8 benchmarks) F1 0.8555 Qwen3Guard-Gen-8B-strict: 0.8604

Streaming safety (3 benchmarks) R-AUC / T-AUC 0.9858 / 0.9295 Qwen3Guard-Stream-8B-strict: 0.9640 / 0.8893

Hallucination detection (6 benchmarks) AUC 0.7904 DRIFT: 0.8000

Deployment characteristic Result

Benign-response false-positive rate 0.05% average across 5 datasets

Decode overhead < 0.5%

Quick Start

SingProbe is supported through the SGLang integration branch or vLLM integration branch. Load the probe by its Hugging Face ID at server launch:

python -m sglang.launch_server \ --model-path stepfun-ai/Step-3.7-Flash \ --probe-ckpt inclusionAI/Step-3.7-Flash-singprobe \ --port 30000

The integrations return one score dictionary per generated token (label_0–label_9). Use the exact base-model/probe pair: stepfun-ai/Step-3.7-Flash with this checkpoint.

Citation

@article{singteam2026singprobe, title = {SingProbe Technical Report}, author = {Sing Team}, journal = {arXiv preprint arXiv:2608.30703}, year = {2026}, }